Apprendimento automatico (ML) Jobs

More details: What type of fashion tech MVP are you looking to build? virtual try on with fit prediction What key features do you want in your virtual try-on system? Size and fit prediction What type of size and fit prediction functionality do you need? Measurement-based predictions, User profile customization

CLOUD-NATIVE SUPTECH PLATFORM Developer Implementation Master Specification (PoC Build Pack) 1. PURPOSE OF THIS DOCUMENT This document provides the complete technical build specification for developers implementing the Cloud-Native Regulatory System (CNRS) — a supervisory technology platform for central bank supervision, risk analytics, compliance monitoring, early-warning systems, fraud detection, and stress testing. The platform is cloud-native (AWS), modular, AI-enabled, and supports regulatory analytics aligned with Basel III, AML/CFT, and Risk-Based Supervision frameworks. 2. SYSTEM OBJECTIVES The system must: Ingest regulatory data from financial institutions securely Validate, store, and process supervisory datasets Compute prudential ratios and compliance rules Detect fraud...

I already have a working object-detection pipeline written in Python, and I now need that same logic moved into a cleaner, better-structured Python codebase that’s easy to maintain and integrate into a larger application. Think of it as a conversion/refactor: exact same model, exact same results, but with modern syntax, clear separation of concerns, and thorough inline comments. You’ll start from my original scripts and checkpoints, preserve every bit of accuracy, and hand back a fully functioning module (including a simple demo script) that can be installed with pip-installable requirements. Feel free to streamline library calls—TensorFlow, PyTorch, OpenCV, or whatever is currently in place—so long as the final inference output matches the reference I provide. De...

I’m in the development phase of an Azure Machine Learning project and need a seasoned practitioner to mentor me through model training and evaluation. The workspace is set up and the data is in place; what I’m looking for now is practical, hands-on coaching that will leave me confident about every line of code I run. Using Python and the Azure ML SDK, you’ll help me: • Refine and execute training scripts, choose the right compute targets, and organise experiments. • Build an evaluation workflow that logs metrics, registers the best model, and makes results easy to visualise and share. We’ll work through shared sessions(need to check if this can be shared) and brief code reviews, with you explaining the reasoning behind each step so I can replicate the pr...

Task Summary: Validation for LBP and SVM methods. Created a manual calculation simulation that proves my system's workflow, from image input to classification decision. The system uses the following methods: Feature Extraction: Local Binary Pattern (LBP). Classification: Pre-trained Support Vector Machine (SVM). IMPORTANT: You will NOT be asked to retrain the model or recode it. Your task is to analyze the mathematics behind the model's predictions for just one data sample so that it can be written in the report. Data & Files I Will Provide: -Original Video File (.mp4): I will provide the video. -Validation Matrix: For manual calculations in Excel, you can simply sample a small area (5x5) of the face to demonstrate the LBP (Thresholding & Binarization) formula. There is...

I have a small batch of images—fewer than one-hundred—that need clean, consistent object-detection labelling. For each image you will draw tight, non-overlapping bounding boxes around every instance of the target classes I will supply once we start. Accuracy matters more than speed; missed objects or sloppy boxes will be rejected. Preferred workflow is any modern tool that can export to COCO JSON or Pascal-VOC XML, as these formats plug straight into my training pipeline. If you normally use LabelImg, CVAT, Supervisely, or similar, that’s perfect. Deliverables • Annotated dataset in COCO JSON or Pascal-VOC XML (your choice, just stay consistent). • A quick text report summarising class counts and any edge cases flagged during labelling. I will run a...

I already have a working Python script that identifies stripe-like patterns in still images, but it needs to move from “proof-of-concept” to a polished, deployable module. The current model does a reasonable job on simple samples, yet its accuracy drops with noisy backgrounds, it only understands a handful of stripe geometries, and it processes large batches slower than I’d like. The brief is straightforward: • Improve accuracy: fine-tune the existing algorithm—or replace it—so it handles challenging lighting and mixed-texture scenes without a spike in false positives. • Add more pattern types: extend recognition beyond the basic horizontal/vertical stripes to oblique, curved, or irregular banding the current code ignores. • Optimize perfor...

I have safety sector time-series dataset that combines three synchronized streams: sensor imagery, textual maintenance logs, and high-frequency numeric readings. The objective is to forecast future values—not merely detect anomalies—so grid operators can anticipate demand, equipment stress, and renewable supply fluctuations. Because this is a research-level effort, I’m not looking for an off-the-shelf CNN, RNN, or simple transformer stack. I need a genuinely novel architecture (or a rigorously justified adaptation of cutting-edge multimodal papers) that fuses image, text, and numeric signals into a single forecasting pipeline and demonstrably outperforms strong baselines. Key expectations • End-to-end experimentation code (Python, PyTorch or TensorFlow) with clea...

I have a kaggle dataset containing colored images and thermal image .. do feature extraction and then combine them and the do feature extraction on it

I have safety sector time-series dataset that combines three synchronized streams: sensor imagery, textual maintenance logs, and high-frequency numeric readings. The objective is to forecast future values—not merely detect anomalies—so grid operators can anticipate demand, equipment stress, and renewable supply fluctuations. Because this is a research-level effort, I’m not looking for an off-the-shelf CNN, RNN, or simple transformer stack. I need a genuinely novel architecture (or a rigorously justified adaptation of cutting-edge multimodal papers) that fuses image, text, and numeric signals into a single forecasting pipeline and demonstrably outperforms strong baselines. Key expectations • End-to-end experimentation code (Python, PyTorch or TensorFlow) with clea...

Lead AI / Fullstack Engineer — Project "AZIZA" (Voice-to-Voice AI) ​Project Name: AZIZA Format: Project-based / Remote (with access to local GPU clusters) Tech Stack: PersonaPlex (Moshi-based architecture), PyTorch, TensorRT-LLM, FastAPI, WebRTC, Telegram Mini App (TMA). Hardware Location: Uzbekistan & Turkey clusters powered by NVIDIA L40S ​Project Overview ​AZIZA is an innovative multimodal "Speech-to-Speech" (S2S) ecosystem designed to simulate natural human interaction. We are building an AI assistant that seamlessly transitions between roles: an expert tutor (Chemistry, History, Biology), an empathetic companion, and a simultaneous translator. By processing audio tokens directly, the system achieves unprecedented interaction speeds. ​Current Status: The ...

I need a production-ready object detection model built, trained, and packaged so it runs smoothly on iOS and Android devices, in a modern web browser, and as a lightweight desktop application. The same model should power every platform to keep accuracy and behaviour consistent. You are free to choose the framework you are most comfortable with—TensorFlow, PyTorch, YOLOv8, Detectron2, or another proven library—as long as the final artefacts meet these requirements: • Mobile: optimised builds (e.g. TensorFlow Lite, Core ML, or ONNX) that hit realtime speeds on mid-range phones. • Web: WebAssembly/WebGL or implementation that loads in under three seconds on a standard connection. • Desktop: a small executable or Python app with GPU support when available and ...

I am embarking on a full-stack build of a humanoid companion robot whose number-one mission is caring for an infant from birth through age five. Beyond the usual chore-support and graceful household navigation, the robot must excel at three core caregiving abilities: • Feeding – from bottle to basic solids, with portion control, temperature checks, and spill detection. • Diaper changing – autonomous removal, cleaning, and secure re-diapering, tracked in a hygiene log. • Health monitoring – continuous vitals, posture, and environmental safety checks, with instant mobile alerts. Rich, natural interaction is essential. The robot should talk and sing lullabies, entertain with simple games, and read stories or show age-appropriate educational content...

I already have two live avatars that mirror real people as they speak to one another, yet the current pipeline adds several seconds of lag. I need your help driving total end-to-end latency (mouth movement, facial animation, and generated voice) down to a hard ceiling of one second while keeping everything completely self-hosted—no paid APIs or usage-based services. The finished solution must plug straight into my existing platform and remain free for the public to use. You will begin by profiling the present stack, spotting where frames or audio buffers pile up, then redesign the generation and streaming loop so that speech-to-text, text-to-speech, facial blend-shape synthesis, and video compositing all run in near real time. GPU acceleration, WebRTC, low-level ffmpeg calls, on-dev...

The project centres on building a production-ready text-classification pipeline that leverages modern deep-learning techniques. I have a labelled dataset and need end-to-end code that ingests the text, handles cleaning and tokenisation, and trains an accurate classifier. Python is the preferred language; using PyTorch, TensorFlow or another mainstream framework is fine as long as the solution is reproducible and easy to extend. Key deliverables: • Well-commented source code (data loading, model, training loop, evaluation) • Clear instructions to run training on a fresh machine (README or notebook) • Metrics report showing accuracy, precision, recall and F1 on a held-out set • Exported model weights and a small inference script or API endpoint for batch prediction...

I need a partner who can walk me through the full process of quantifying and explaining feature importance across several classic models—specifically Linear Regression, Decision Trees and Support Vector Machines—using Python. The goal is to compare and contrast interpretability techniques such as SHAP, LIME, PDP and ICE, then package the findings so that non-technical stakeholders can easily understand why each feature matters. What I expect from you • Well-structured, reproducible Python code (preferably in Jupyter notebooks) showing how each model is trained and how the above interpretability methods are applied. • Clear visualisations and narratives that highlight where and why the different methods agree or diverge. • At least one live session (Zoom, M...

It is a Master level project, I want you to do it from the start where thing should be done by like research, getting required datasets, coding, project report and etc.. what the project looks like is that, it should be a interactive program where it's predicts the CO2 emissions of each county in ireland like what would be the CO2 emission tomorrow based on the energy consumption, real time weather data of that county. If the county's CO2 emission is high then the county should be red, if medium then yellow and if low then green. All this should be using 3D digital twins visualization and prediction, use Cesium pipeline.

We are launching a gamified, project-based platform that empowers teams to solve environmental, social, and economic challengese. To move from concept to scalable reality, we hands-on AI project an architect who can help us implement our AI strategy. The ideal resource will be a MEAN stack/Python developer. You will be helping us create and implement the following: • An adoption roadmap that ties specific AI capabilities to each stage of our workflow and project milestones, showing where automation, prediction, or generative content delivers the most value. • A reasoned “why this, not that” selection of tools—think Hugging Face transformers versus OpenAI GPT-4, TensorFlow or PyTorch for model training, spaCy for NLP, Vision APIs for image tasks—plus ra...

Hiring Freelancers – AI / Computer Vision & Edge Systems Confidential Enterprise Project (NDA Required) We’re looking to engage a few experienced freelancers for a confidential, enterprise-grade technology project involving computer vision and edge AI. The work is part of a real production deployment (not a research project or demo). Detailed project information will be shared only after shortlisting and NDA signing. Engagement Details Type: Freelance / Contract Duration: ~3–4 months (extension possible) Commitment: Full-time preferred (role dependent) Work mode: Remote (India preferred) Start: Immediate / near-term Open Roles 1. Computer Vision / Machine Learning Engineer What we’re looking for: Hands-on experience with object detection / visual recognition Exp...

INGENIERO SENIOR DE IA: SISTEMA RAG MULTIMODAL ON-PREMISE CON APRENDIZAJE CONTINUO 1. CONTEXTO Y DESAFÍO REAL proyecto del sector de la trefilería y el galvanizado con más de 40 líneas de producción activas. desafío no es la falta de información, sino que el conocimiento crítico es volátil: reside en la experiencia de supervisores y operarios veteranos y se transmite de forma verbal. Cuando surge una solución técnica en planta, esta no se documenta y se pierde para el siguiente turno. Buscamos desarrollar un ecosistema de IA que no solo responda preguntas, sino que capture y democratice el conocimiento técnico que surge en el día a día. 2. LA SOLUCIÓN: "THE KNOWLEDGE LOOP" B...

I need a production-ready object detection model built, trained, and packaged so it runs smoothly on iOS and Android devices, in a modern web browser, and as a lightweight desktop application. The same model should power every platform to keep accuracy and behaviour consistent. You are free to choose the framework you are most comfortable with—TensorFlow, PyTorch, YOLOv8, Detectron2, or another proven library—as long as the final artefacts meet these requirements: • Mobile: optimised builds (e.g. TensorFlow Lite, Core ML, or ONNX) that hit realtime speeds on mid-range phones. • Web: WebAssembly/WebGL or implementation that loads in under three seconds on a standard connection. • Desktop: a small executable or Python app with GPU support when available and ...

I need expert assistance in integrating AI and ML into the execution and monitoring of an oil and gas capex project. Key focus areas: - Project scheduling optimization - Cost engineering Ideal Skills and Experience: - Background in oil and gas industry - Expertise in AI/ML applications - Strong project management skills - Experience in cost engineering and financial analysis Looking for someone who can provide innovative solutions to enhance efficiency and reduce costs.

I am just getting started with Python and would like a patient tutor who can guide me step-by-step, answer my questions as they come up, and help me practise writing clear, working code. The main areas I need to master are: • Basic syntax and data types • Control structures and functions • Libraries and modules Please structure the lessons so each concept is demonstrated with short examples, followed by hands-on exercises I can share back for review. I am happy to work in whichever environment you prefer—IDLE, VS Code, Jupyter Notebook—so long as I can replicate the workflow on my own machine. By the end of our time together I should be comfortable writing small scripts, understanding error messages, and knowing where to look next when I get stuck....

Project Overview This proof-of-concept will demonstrate a regulator-grade, fully secured VPC hosting a central authority and multiple financial-institution tenants, while automating supervision and compliance checks using native AWS services. Scope The environment will be logically segmented into public and private subnets for each participant. The central authority resides in its own network segment and can observe, query, and enforce policies across all other institutions without exposing sensitive resources publicly. Key Services AWS Lambda for event-driven oversight logic and scheduled compliance sweeps AWS RDS for the authoritative supervisory data store AWS S3 as the immutable audit and reporting repository Security & Compliance Networking, IAM, logging, encr...

I am building an intrusion-detection system that relies on entropy-based calculations applied over time windows to flag anomalous behaviour in user activity data. The goal is to detect subtle, previously unseen patterns rather than match against known signatures, so the core of the work is an efficient entropy engine that continuously ingests, time-stamps, and scores each event stream for deviation. My data source will be raw user-activity logs—login records, file interactions, command histories, and similar feeds collected from endpoints and servers. You may assume the logs arrive in near-real time (JSON or CSV) and contain at least a timestamp, user identifier, and event type. The system should: • Parse and normalise each record, maintaining a rolling history per user and fo...

I need a complete Python application that runs on a Raspberry Pi 5 and identifies plant-leaf diseases in real time from the Pi camera. The same core model must also accept still-image uploads. All three disease categories—Fungal, Bacterial and Viral—have to be recognised with reliable accuracy. The user interface will be a Django web app. Within that app I want three role levels—Admin, Standard user and Guest—each with appropriate permissions for running detections, reviewing results and managing data. Please structure the code so that REST endpoints are cleanly separated; this will let me expose the following Android-ready APIs later on: live-video analysis, image-file analysis and retrieval of disease-history logs. Deliverables • Python inference engine (...

Job Description: Senior Python Developer (AI/ML Project) We are hiring a Senior Python Developer to work on an AI-focused project. The ideal candidate has strong hands-on Python experience, is comfortable working within existing GitHub repositories, and has exposure to practical AI/ML integration and evaluation workflows. This role requires an experienced developer who can write high-quality code, actively review and mentor others through code reviews, and collaborate with cross-functional teams involved in AI model usage and improvement. Key Requirements • 3-14 years of hands-on Python development experience • Strong day-to-day experience with GitHub, including: Pull requests, code reviews, and team collaboration Version control in distributed teams. Hands-on CI/CD pipeline imp...

I need a clear, well-structured Python pipeline that ingests JPEG road images and their corresponding lane-segmentation masks (they sit in two separate folders sharing the same filenames) and returns one scalar per frame: a normalized lane-visibility score. The number is meant for relative comparison only, so internal units do not have to match any physical standard—just remain self-consistent frame to frame. The logic I have in mind revolves around four cues: • Brightness of the lane pixels themselves • Contrast between those pixels and adjacent pavement pixels • A distance weighting that values pixels closer to the camera more heavily than distant ones • A continuity penalty that reduces the score when the mask reveals breaks or flicker in the lane lin...

We are looking for a Senior AI/ML Engineer (LLM Training and Deployment). We are building Health Model, an on-prem "Robust Expert" LLM that generates healthcare interoperability code from natural language. The model should generate Mirth Connect (NextGen Connect) channel XML and JavaScript transformer code and support HL7 v2 and FHIR patterns. No PHI will be used. Only public docs, open-source samples, and synthetic messages. We need a strong developer to implement the end-to-end pipeline: dataset ingestion, synthetic instruction generation, LoRA fine-tuning, validation harness, and local deployment with an OpenAI-compatible API. Target compute is on-prem GPU hardware (DGX Spark class). Optional experiments can run on Google Vertex AI credits. [Required Skills] - LLM fine-tuni...

I'm seeking an AI expert to automate tasks in the finance sector. Key requirements include: - Developing AI solutions to streamline finance operations - Expertise in machine learning and data processing - Experience in the finance industry is a plus Ideal skills and experience: - Proven track record in AI automation - Strong background in finance - Ability to deliver efficient, scalable solutions Please share relevant experience in your application.

We' re actively seeking a special strategic individual and proven app developer to collaborate with Encyclomedia on the creation of a next-generation, AI-enhanced platform designed to transform how media planning, audience intelligence, and performance optimization are executed in today’s data-driven environment. This is not a typical build request. It is an opportunity to co-develop (as a potential partner) a flagship product positioned for market leadership, backed by Encyclomedia’s deep expertise in media strategy, analytics, and measurable ROI. With more than three decades of experience serving blue-chip brands, agencies, and media organizations, we bring validated market demand, industry relationships, and a clear commercialization pathway. The app will integrate ad...

I have a steady stream of plain-text machine logs arriving every hour. What I need is a dependable way to sift through each file, detect the anomalous patterns hiding in the noise, and produce a cleaned log (or at least clearly flagged lines) before the next batch rolls in. The raw files are straightforward TXT—no embedded markup or JSON structures—so the solution can focus entirely on pattern analysis rather than parsing exotic formats. Because the anomalies are behavioural rather than simply extreme numeric values, the detection logic must look for irregular sequences, unexpected combinations of fields, or sudden structural deviations. I’m happy with a Python‐based approach (pandas, scikit-learn, PyOD, or similar libraries come to mind), but I’m open to anothe...

I want to launch an Android-only application that showcases property listings and layers in practical AI assistance to make the experience smarter for both managers and renters. At its core the app must let a property manager add, edit, and remove listings (images, price, availability, basic details). The AI component should work behind the scenes—think auto-tagging amenities from photos, suggesting competitive pricing ranges, or surfacing the most relevant homes to a tenant based on their previous in-app behaviour. I’m open to the exact technique you use (TensorFlow Lite, ML Kit, embedded models, or a lightweight cloud call), so long as it stays responsive on typical mid-range Android devices. No third-party property-management or CRM integrations are required; the app should...

I want to embed a minimax-driven AI agent into my existing web application so it can take over day-to-day Development – Website Management duties. Rather than the usual rule-based scripts, the bot should evaluate alternative actions with a minimax search and choose the best move for the site at any given moment. Below are the specific website management areas the agent must cover: • Content updates • User interactions (comments, queries, basic moderation) • Performance monitoring (speed, uptime, error trends) • Routine website updates and patches You’ll design the decision logic, implement the agent (Python, Node, or another modern stack is fine), connect it to my CMS/backend APIs, and deploy it to production on the same hosting stack that serves...

A comprehensive literature review on recent developments in artificial intelligence is required for a science-focused research paper. The goal is to synthesise peer-reviewed work published roughly between 2020 – 2024, highlight prevailing trends, identify research gaps, and propose future directions. No experimental data collection or purely theoretical exposition is needed—this piece is strictly a literature review. I will supply a preliminary outline and a small set of key papers. You will expand the search using scholarly databases (Google Scholar, IEEE Xplore, ACM Digital Library, Scopus) and apply clear inclusion/exclusion criteria. Please organise the discussion around major AI sub-fields—such as deep learning architectures, reinforcement learning, ethical AI, and ...

I am looking to develop a decision-support algorithm that identifies and ranks the best production options across locations, varieties and time windows, based on a large set of variables. The model should evaluate each option using economic factors (costs, prices, margins), agronomic performance (yield, quality, timing reliability), logistics (distance to market, transit time, reliability), and risk (climate, water, regulatory, operational). The algorithm must first eliminate non-viable options using hard constraints (e.g. feasibility, minimum thresholds), and then score and rank the remaining options using a weighted, configurable logic that produces a single comparable score per option. The goal is not pure prediction, but a transparent and scalable optimization engine that supports bett...

I want an Android app that SIMULATES crash game behavior for PROBABILITY ANALYSIS purposes. Requirements: - Simulated crash rounds based on probability models - Streak & volatility analysis - Auto-generated signals (Low / Medium / Avoid) - Target outcome accuracy around 75%

I need AI trainer. The goal is to arrive at production-ready machine-learning models. You will receive full access to the data, a brief describing the business context behind each task. What matters most is a clear, well-documented workflow: data cleaning, feature engineering, model selection, hyper-parameter tuning, cross-validation, and benchmark reporting. I also need concise guidance notes so my in-house team can rerun or extend the work later. Deliverables • Trained model files saved with versioning and clear naming • A short report (PDF or Markdown) summarising methodology, metrics, and next-step recommendations I’ll be available for quick feedback cycles and can spin up extra compute if needed. Let’s turn this diverse data into smart, reliable insights.

I’m wrapping up my final-year project and need an AI module that can generate truly personalized workout plans. The focus is narrow and clear: every plan must be driven by the user’s stated fitness goal of “improving overall fitness.” I’m not looking for real-time form feedback or progress analytics at this stage—just rock-solid plan generation that feels tailored, practical, and evidence-based. Here’s the flow I have in mind. A user enters basic profile data and selects “Improve overall fitness” as a goal. Your algorithm interprets that goal, selects appropriate training modalities, adjusts intensity and volume to suit beginner through intermediate levels, and outputs a structured weekly routine (exercises, sets, reps, rest, and optio...

Project Title: Custom Offline AI Educational Chatbot (Curriculum-Based RAG) Project Overview I am looking for a developer to create a customized AI chatbot designed for students. The primary goal is to provide a "tutor in a box" that contains a vast knowledge base of specific educational curricula (textbooks, PDFs, and related materials). Critical Requirement: The system must function entirely offline after the initial setup, allowing students in areas with no internet access to interact with the AI and receive accurate answers based on the uploaded curriculum. Key Features & Requirements * Offline Functionality: The chatbot must run on local hardware (e.g., a laptop, Raspberry Pi, or a high-end tablet) without needing an internet connection. * Custom Knowledge Base (RAG): ...

I want to create a custom open AI like Claude, ChatGPT,Gemini etc so I can use for my internal use where I just need to upload customer documents and AI will give full 6-7 pages colurful report with our company logo with below mentioned details Loan eligibilty Details in Tabular Form in Tabular Form documents form Filling Details queries based on Past queried data

I want to create a custom open AI like Claude, ChatGPT,Gemini etc so I can use for my internal use where I just need to upload customer documents and AI will give full 6-7 pages colurful report with our company logo with below mentioned details Loan eligibilty Details in Tabular Form in Tabular Form documents form Filling Details queries based on Past queried data

The file in question is a single screenshot whose text is now so heavily blurred that it is impossible to read. My only goal is to recover that text with enough clarity that every character can be copied or transcribed without guesswork. Because the blur is severe, I expect advanced de-blurring techniques—whether that means frequency-domain restoration in Photoshop, AI-powered tools such as Topaz Sharpen AI/Gigapixel, or custom Python/OpenCV scripting. Feel free to combine multiple passes or layer-based masking if that gives the best result; I just need the cleanest, most legible outcome you can achieve. Deliverable: a high-resolution image (PNG or TIFF) where the text is crisp and readable. If the restored file must remain at its original dimensions, please provide a second upsc...

Project Title: AI-Based "Digital Arrest" Scam Detection System (MVP) Project Overview: I am looking for an AI/ML developer to build a functional prototype of a security system designed to detect "Digital Arrest" scams. The system needs to analyze video and audio inputs in real-time (or near real-time) to identify deepfakes, threatening language, and fake law enforcement visuals. Key Features Required (The Scope): I need a desktop-based prototype (Python/Streamlit or similar) that can process a sample video feed or live webcam input and perform the following: * Audio Threat Detection (NLP): * Transcribe audio in real-time (using OpenAI Whisper or Google Speech-to-Text). * Detect specific scam keywords/intents (e.g., "money laundering," "CBI," &...

I want to build a voice-only AI companion app for India. The experience should feel like a phone call with a friend. Core requirements: Full voice conversation (no typing) Real-time speech-to-speech Emotional support + life/business guidance Basic medical information (no diagnosis, no prescription) Multi-language support (start with Telugu + English) IMPORTANT: I am not technical I want a working demo/prototype first Android app preferred Please apply ONLY if: You have already built voice AI apps You can show a demo / GitHub / video You understand low-latency voice conversation Budget: To be discussed after demo.

Responsible for initiating the implementation and application of Data Science strategies to enhance company results. Some of the projects developed: - Time Card Information Extraction Automation via OCR Developed an OCR pipeline to automatically extract and process information from time cards and integrate it into the company's system; Reduced processing time and minimized manual errors in employee time management; - Intelligent Chatbot for Internal Support Modeled an intelligent chatbot trained on the company manual, utilizing LLMs with optimized prompts, Transformer-based architecture via Hugging Face, RAG (Retrieval-Augmented Generation) approach, Redis for context caching, and Gunicorn as the application server for production; - Inventory Prediction and Purchasing Optimization...

The opportunity At Smartmoney Wealth Management, we’re building technology to make money clear, visible, and actionable in a world where finances are increasingly digital and fragmented. Alongside our core advice business, we have already commenced building a new AI-driven financial intelligence platform. The next phase is execution — getting it live, reliable, and delivering real outcomes. We’re looking for an experienced AI Solutions Engineer to help finish, deploy, and scale this platform, while also applying AI to improve internal processes across the Smartmoney business. The role This is a hands-on execution role. You will: Take an already-started AI platform and get it live and working correctly Build, refine, and deploy AI systems using real financial and pro...

use the tools API's and SDK's on to build an AI agent

I have a large collection of raw audio recordings and need an expert who can turn them into a high-performing voice model inside Amazon SageMaker. Your job starts with designing an efficient preprocessing pipeline—cleaning, segmenting, and augmenting the audio so that the data is ready for distributed training on SageMaker. Once the data is prepared, I’d like you to select or build a state-of-the-art architecture, train it end-to-end, and fine-tune until we hit 90-95 % word-level accuracy on my validation set. Please incorporate best-practice techniques such as mixed-precision training, hyper-parameter tuning jobs, and automatic model versioning so we can reproduce results later. Finally, the trained model must be packaged as a SageMaker endpoint that plugs directly into ...

I'm seeking an experienced fractional CTO to guide our machine learning initiatives. We have a ready-to-use dataset and need assistance with: - Model Development: Designing and building ML models. - Data Preprocessing: Preparing data for optimal model training. - Performance Tuning: Enhancing model accuracy and efficiency. Ideal Skills & Experience: - Expertise in Machine Learning - Proven track record in model development - Strong data preprocessing skills - Experience in performance tuning of ML models - Leadership experience in tech projects Looking for someone to ensure our project is on the right path and achieves its goals efficiently.