Jobs ML / AI Engineer

Join our team as a Machine Learning Engineer, shaping the future of Generative AI with cutting-edge demos, scalable architectures, and hands-on development.

 We’re looking for a passionate Machine Learning Engineer to join our team and dive into the exciting world of Generative AI.  You’ll get hands-on experience with cutting-edge demos and proof of concepts (POCs), turning bold ideas into reality. The ideal candidate has solid Back-end engineering skills and is curious about Generative AI development. If you’re familiar with MLOps, large language models (LLMs), or concepts like Retrieval-Augmented Generation (RAG) is a plus, as is experience with Front-end languages! Experience in the Financial Services domain, particularly Banking, will be a big plus. 

You will be exposed to a variety of tasks, including: 

• Develop proof of concepts (PoC). Test and validate new ideas 
• Drive implementation. Optimize and transform data solutions to improve business outcomes 
• Help with proposals as a technical consultant.  

Job Description

• Assist in building and testing Generative AI demos and POCs 
• Support the design of simple, scalable architectures for Generative AI applications 
• Work with team members to integrate AI components into larger systems 
• Use MLOps practices to help automate parts of the model development process 
• Follow guidelines to ensure that Generative AI applications are secure and meet basic governance standards 
• Help deploy AI applications on cloud platforms or on-premises setups with team support 
• Adapt to a fast-paced environment with evolving project needs 
• Keep up with AI trends and apply them to projects with guidance 
• Advise clients. Understand their needs, analyze possible solutions, and present the best options 

Qualifications

• 4+ years of experience in IT industry, with at least 2-3 years of experience in machine learning 
• Solid Back-end engineering skills, particularly with Python (e.g., Django, Flask, or FastAPI). 
• Experience with pre-sales activities and opportunity processing 
• Basic experience with databases or tools like vector databases (e.g., Pinecone, Weaviate, Faiss) 
• Familiarity with AI frameworks such as TensorFlow, PyTorch, or Hugging Face 
• Understanding of CI/CD pipelines  
• Knowledge of RAG or AI application fundamentals (security, governance, etc.) 
• Experience with cloud platforms (AWS, Google Cloud, Azure) or on-premises setups 
• Ability to solve problems and handle shifting priorities with team support 
• Experience with client-facing roles 
• Ability to demonstrate ideas and solutions clearly and confidently 
• Bachelor's or Master's degree in computer science, machine learning, artificial intelligence, or a related field 

• Upper-Intermediate level of English 

   

  Would be a plus

• Knowledge of other programming languages, such as Java or Go 
• Experience with open-source projects or exposure to tools, such as Airflow or Spark 
• Familiarity with containers (e.g., Docker) or orchestration tools (e.g., Kubernetes) 
• Experience in the Banking and Financial Services domain  
• Experience with prompt engineering or fine-tuning LLMs 

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.

Skills requirements:
• Strong Python Experience (2 year +);
• Experience with LLM , Diffusion models;
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

Key responsibilities:
• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

We are looking for a Senior Data Scientist with strong technical expertise and a practical mindset to work on complex data-driven challenges. In this role, you will design and implement ML and GenAI solutions, experiment with modern approaches, and transform ambiguous business problems into scalable, production-ready systems.

Requirements
Must-have

• 4+ years of experience in Data Science
• 4+ years of hands-on experience with Python
• Strong understanding of Machine Learning fundamentals, including:
  • regression and classification models
  • feature engineering and model evaluation
• Practical experience with LLMs and GenAI, including:
  • GPT / ChatGPT or similar LLMs
  • LangChain
  • Retrieval-Augmented Generation (RAG)
• Experience with EDA, data preprocessing, and basic dimensionality reduction (e.g. PCA)
• Hands-on experience with tree-based models (e.g. XGBoost)
• Experience building scalable and high-load solutions
• Ability to write clean, maintainable code
• Participation in technical and architectural decisions
  
  Nice to have
• Experience with NLP libraries (SpaCy, Hugging Face)
• Understanding of Explainable AI (XAI) and model interpretability
• Experience with cloud platforms (AWS / GCP / Azure)
• Ability to translate business problems into ML solutions

• Background in R&D, experimentation, or prototyping

  
  Key Responsibilities

• Design and develop scalable Data Science and GenAI solutions aligned with business goals.
• Build, evaluate, and optimize ML models, including:
  -linear models
  -gradient boosting (XGBoost)
  -NLP and LLM-based solutions
• Develop and productionize LLM-powered applications using LangChain and RAG approaches.
• Perform EDA, feature engineering, dimensionality reduction (PCA), and model evaluation.
• Apply XAI techniques to ensure model transparency and explainability.
• Contribute to data science architecture and solution design.
• Write clean, maintainable code and participate in code and design reviews.
• Optimize performance and reliability of high-load systems.
• Conduct R&D activities: explore new ML/GenAI techniques and assess their practical impact.
• Collaborate with engineering, product, and business teams to deliver impactful data-driven solutions.
  
  We offer:
• Great networking opportunities with international clients, challenging tasks;
• Building interesting projects from scratch using new technologies;
• Personal and professional development opportunities;
• Competitive salary nominated in USD;
• Paid vacation and sick leaves;
• Flexible work schedule;
• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

   

Role Overview

Designs and implements the visual feature extraction pipeline, ensuring high-quality input data for the ML model from multi-camera capture system

Key Responsibilities

Phase 0: Pilot 

• Design and deploy 3-camera capture system (top-down + 2 oblique)
• Implement cross-polarized lighting setup for glare elimination
• Develop visual feature extraction algorithms:
  • Skin blanching detection
  • Contact patch area measurement
  • Finger flexion analysis (keypoint tracking)
  • Micro-tremor detection (10-20 Hz)
• Synchronize camera streams with hardware frame-lock
• Collect and curate training dataset (100+ matches)

Phase 1: Demo 

• Optimize feature extraction for real-time performance (<8ms budget)
• Implement confidence scoring for feature quality
• Handle challenging conditions (varied lighting, athlete positioning)
• Support broadcast integration with visual debugging tools
• Refine calibration procedures based on demo feedback

Phase 2: Production 

• Implement failover and redundancy for camera failures
• Optimize for 98%+ uptime during live events
• Develop automated quality monitoring and alerting
• Support LED synchronization (Art-Net/DMX integration)

• Production-grade error handling and recovery

   

Required Technical Skills

Must Have:

• 5+ years experience in computer vision engineering
• Expert-level knowledge of OpenCV and image processing techniques
• Experience with high-speed camera systems (120+ FPS)
• Strong understanding of optical phenomena (lighting, polarization, color science)
• Experience with multi-camera synchronization and calibration
• Proficiency in C++ and Python for real-time CV pipelines

• Experience with GPU-accelerated image processing (CUDA, cuDNN)

   

Strongly Preferred:

• Experience with industrial vision systems or broadcast/entertainment applications
• Knowledge of color-based feature extraction (blanching, perfusion analysis)
• Experience with pose estimation and hand/finger tracking (MediaPipe, OpenPose)
• Background in optics and lighting design for machine vision
• Experience with GigE Vision or USB3 Vision camera protocols

• Familiarity with embedded vision systems or edge deployment

   

Nice to Have:

• Experience with NIR imaging or multi-spectral cameras
• Knowledge of photogrammetry and 3D reconstruction
• Experience with motion capture systems or sports analytics
• Background in signal processing for vibration/tremor detection

• Familiarity with broadcast equipment and professional video workflows

   

Required Soft Skills

• Hands-on hardware expertise: Comfortable with physical camera setup and troubleshooting
• System thinking: Understand end-to-end pipeline from optics to ML model
• Attention to detail: Ensure data quality and consistency across diverse conditions
• Pragmatism: Balance theoretical perfection with practical constraints (time, budget)

• Field readiness: Willingness to travel for on-site deployments (2-3 trips to US)

   

Success Metrics

• Camera system operational with <0.1% frame drop rate
• Feature extraction latency <8ms (P95)
• Visual features correlate with grip force (0.4-0.7 per signal)
• System handles diverse athlete characteristics (6 Fitzpatrick skin tones)
• 100+ matches captured with synchronized reference data

We are looking for a highly experienced Senior AI/ML Engineer to lead the creation of a next-generation real-time biometric estimation system for global sports broadcasts.

About the Project:
We are building a real-time, non-contact system to estimate athletes’ exertion for live sports broadcasts. Using high-speed video and computer vision, it predicts force metrics with 85%+ accuracy, replacing traditional sensors, with low-latency and robust performance under complex conditions.

Key Responsibilities:

Phase 0 – Pilot

• Design ML architecture for grip estimation
• Train initial model (force sensors + video data)
• Build training & data labeling pipeline
• Validate across diverse athlete profiles
• Achieve 75%+ correlation

Phase 1 – Demo

• Refine model using demo event data
• Implement 2-second per-athlete calibration
• Optimize for edge cases (skin tones, hand sizes)
• Achieve 80%+ correlation

Phase 2 – Production

• Improve accuracy toward 85%+
• Optimize inference to <40ms (P99)
• Implement advanced scoring features

• Production hardening & reliability improvements

   

Required Skills:

• 5+ years of experience in applied machine learning/deep learning
• Strong background in computer vision and image-based regression tasks
• Hands-on experience with PyTorch or TensorFlow for production systems
• Experience with real-time inference optimization (TensorRT, ONNX Runtime)
• Understanding of signal processing and temporal data analysis
• Experience training models on diverse datasets (handling bias, data augmentation)

• Proven track record achieving high-accuracy requirements (>80% on complex tasks)

   

  Strongly Preferred:

• Experience with biomechanical or physiological signal estimation
• Knowledge of optical/visual phenomena (skin blanching, perfusion, micro-tremors)
• Experience with few-shot learning or transfer learning approaches
• Background in sports analytics or human performance monitoring
• Experience with active learning for iterative model improvement

• Published research or patents in computer vision/ML domains

   

  Nice to Have:

• Experience with NIR (near-infrared) imaging or multi-spectral analysis
• Knowledge of pose estimation frameworks (MediaPipe, OpenPose)
• Experience with edge ML deployment on NVIDIA platforms
• Familiarity with time-series forecasting or sensor fusion

Soft Skills:

• Technical leadership: Ability to make critical architectural decisions under uncertainty
• Problem-solving: Creative approaches to novel ML challenges (no precedent for optical grip estimation)
• Communication: Clearly explain complex ML concepts to non-technical stakeholders
• Adaptability: Rapid iteration based on real-world performance feedback
• Ownership: Take full responsibility for model accuracy through systematic experimentation

We are seeking a highly skilled and motivated Machine Learning Developer to join our dynamic team, focusing on developing, deploying, and optimizing Large Language Models for chatbot applications. This role involves working on cutting-edge AI technologies to create conversational agents that provide engaging and insightful interactions with users. The ideal candidate will have a strong background in machine learning, Natural Language Processing, and experience in developing LLM-based chatbots.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• +5 years of experience in machine learning and NLP, with a focus on developing applications using LLMs.
• Proficiency in programming languages such as Python and frameworks/libraries like TensorFlow, PyTorch, Hugging Face Transformers.
• Experience with cloud services (AWS, Azure, GCP) for deploying ML models and applications.
• Strong understanding of RESTful APIs for integrating chatbot functionalities into different platforms.
• Familiarity with version control tools (e.g., Git) and ML development tools (e.g., Jupyter Notebooks, MLflow).
• Participate in pre-sales activities, including developing ML offering materials and engaging with clients to understand their needs, presenting tailored solutions, and demonstrating the potential impact of our ML technologies.

• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.

   

Preferred Qualifications:

• Knowledge of front-end technologies (HTML, CSS, JavaScript) for crafting interactive chatbot interfaces is advantageous but not required.
• Certifications or advanced training in machine learning, cloud architectures, or similar fields.
• Active participation in relevant tech communities or contributions to open-source projects in the ML/NLP domain.

Job Responsibilities:

• Design and implement chatbot solutions using Large Language Models such as OpenAI GPT API or similar frameworks.
• Collaborate with cross-functional teams to integrate chatbot solutions into existing platforms and workflows.
• Optimize and fine-tune LLMs for performance, accuracy, and user engagement.
• Build and optimized RAG and vectorized databases
• Monitor and evaluate the performance of chatbot applications, identifying areas for improvement and implementing updates.
• Stay up-to-date of developments in AI, machine learning, and NLP to ensure our solutions remain cutting-edge.
• Develop and maintain documentation related to ML models, including model design, deployment details, and performance metrics.
• Work with data engineers to ensure the availability and quality of data for training and fine-tuning models.
• Implement security measures to protect sensitive information processed by chatbots

What we offer:

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

We are looking for a Junior AI / ML Engineer (Generative AI) to join our AI & Data projects. This role is designed for an early-career, AI-native engineer who is comfortable using modern GenAI tools and wants to grow on real projects under the guidance of senior ML / AI experts.
You will help rapidly prototype ideas, build small PoCs, and experiment with solutions based on large language models (LLMs) and other generative AI techniques. Your focus will be to implement well-defined tasks, run experiments, and use GenAI tools to speed up coding, analysis, and documentation – while learning how to do this safely and reliably in production-oriented environments.

Required Qualifications:

• 1–2 years of experience in software development, data science, or ML (commercial experience, internships, or strong personal projects).
• Solid basic skills in Python and core data/ML libraries (e.g., NumPy, pandas, Scikit-learn).
• Understanding of fundamental ML concepts (datasets, train/validation split, basic metrics, overfitting).
• Practical familiarity with generative AI / LLMs:
  - regular use of tools like ChatGPT, Copilot or similar for coding and data tasks;
  - basic understanding of prompts, context windows, and common limitations (hallucinations, privacy, bias).
• High motivation to learn, ask questions, and accept feedback.
• Organized and responsible: able to follow a spec, document work, and meet agreed timelines.

Preferred Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
• Course work, pet projects, or a thesis related to ML, NLP, or Generative AI.
• Basic exposure to RAG, embeddings, or vector databases (from articles, courses, or small experiments).
• Familiarity with at least one cloud platform (Azure, AWS, or GCP) from labs or online coursesю.
• Experience with Jupyter notebooks, Git, and simple CI/CD or MLOps tools (even at a “student project” level).
• Participation in hackathons, Kaggle competitions, or open-source projects.

Job Responsibilities:

• Rapidly prototype and iterate on ML / GenAI ideas in notebooks and scripts, turning high-level concepts into small PoCs and demo flows.
• Implement well-defined tasks in Python (data preprocessing, basic model training, evaluation scripts, and utility functions) as part of prototypes and production-oriented components.
• Assist in experiments with LLMs and GenAI APIs (prompt variants, small workflows, simple RAG setups) under the guidance of senior engineers, proactively suggesting new options and documenting what works and what doesn’t.
• Use GenAI tools to support your daily work (coding, tests, documentation, exploratory analysis) and capture key findings in a clear, structured way.
• Prepare and clean datasets, run experiments, and summarize results in concise formats (tables, short reports, simple dashboards).
• Help build and maintain demo environments and internal PoCs for ML / GenAI use cases, keeping them reproducible and easy to reuse.
• Follow coding standards, version control practices, and basic quality processes (code reviews, simple tests, logging).
• Actively learn from senior team members, ask questions, and gradually take ownership of small components within larger solutions.

Department/Project Description

You will join the projects that apply generative AI to real business problems: intelligent assistants, smarter search and retrieval, content transformation, and decision-support workflows.
You will work in cross-functional teams alongside experienced ML engineers, data engineers, and cloud specialists, with a strong focus on practical skills, rapid prototyping, and mentoring-driven growth in the GenAI space.

We are seeking a Senior AI Engineer to drive the development of AI business agents using the SADK framework. Ideal candidates bring deep expertise in AI/ML/LLMs, RAG pipelines, vector databases, and agent frameworks, with a preference for healthcare/clinical trials experience and compliance knowledge.

The project is centered on the implementation of clinical solutions for pharmaceutical product development and testing.

This is you

• 5+ years in software engineering, including 3+ years with AI/ML/LLMs;
• Expert-level prompt engineering and LLM application development;
• Experience with OpenAI, Anthropic, or Azure OpenAI APIs;
• Strong proficiency in Python and/or TypeScript;
• Hands-on RAG (Retrieval Augmented Generation) implementation;
• Understanding of agent frameworks like LangChain or AutoGen;

• English - Upper-Intermediate level or higher.

   

Nice-to-have skills:

• Domain knowledge in healthcare or clinical trials;
• Experience with Microsoft Agent Framework or similar tools;
• Skills in fine-tuning and model optimization;
• Background in multi-agent systems and workflows;

• Knowledge of 21 CFR Part 11 and GxP compliance.

   

This is your role

• Lead development of business agents using the SADK framework;
• Design agent architectures, including Knowledge, Review, Triage, Workflow, Research, and Recommendation agents;
• Master prompt engineering techniques tailored to clinical use cases;
• Implement RAG pipelines and integrate knowledge bases;
• Optimize agent performance for accuracy, latency, and cost;
• Establish evaluation frameworks and quality metrics for agents;
• Mentor AI/ML engineers on best practices in agent development;
• Collaborate with domain analysts to translate requirements into agent specifications;
• Partner with the Platform Pod to improve SADK and identify new MCP server needs. 

Senior Applied AI/ML Engineer (LLM + Production) — English B2

We’re looking for a Senior Applied AI Engineer to raise the quality of production AI/LLM systems through clear metrics, rigorous evaluation, and fast iteration. This role is for someone who doesn’t guess—you measure, experiment, and ship improvements that move real product outcomes.

What you’ll do

• Improve production AI systems through evaluation, experimentation, and system design
• Build and maintain metrics, baselines, and measurement approaches to track progress
• Debug failures methodically, identify root causes, and iterate toward measurable gains
• Work with LLM systems end-to-end: prompt design, agent workflows, output evaluation, and production integrations

• Write and maintain production code to turn ideas into working systems

   

Tech stack

• Golang — primary production language
• Python — used when needed for ML workflows
• Postgres, Redis, and internal services

You don’t need to be a Go expert on day one, but you should be comfortable reading and modifying production code.

Who we’re looking for

• 3+ years of experience (we’ll consider 3 years if you’re exceptionally strong in AI/ML)
• English: B2

Must-haves

1. Strong AI/ML fundamentals
You understand the theory behind what you build and can choose appropriate methods for a problem.
Examples:

evaluation metrics (precision/recall/F1/etc.)ranking and recommendation conceptsembeddings and similarityexperimentation methodology
Not required:

academic publicationsadvanced theoretical mathlarge-scale model training experience
2. Evaluation-driven mindset You:

think in metrics and baselinesdesign experiments instead of guessingmeasure system improvements quantitativelydebug failures methodicallyThis is the most important signal for the role.

3. Experience with LLM systems you’ve worked with:

prompt designagent workflowsevaluation of LLM outputsproduction LLM integrations
4. Ability to ship production systems
You can:

turn ideas into working systemsiterate based on resultsbalance exploration with delivery
5. Programming ability You’re comfortable writing production code in at least one language (Python, Go, or similar) and learning others when needed.

Nice to have

• Experience improving AI systems after deployment
• Ranking / recommendation systems
• Building evaluation frameworks
• Golang
• Startup or small-team engineering experience
• Computer vision, optimization/constraint-based approaches

Who are we?

Fuel is on a mission to unlock billions of dollars in GDP by helping SMBs make better financial decisions every day. We manage over $500M in customer P&Ls through our FP&A platform, combining AI with hands-on CFO expertise to deliver enterprise-grade finance - without the enterprise price tag or complexity.

fuelfinance.me
instagram.com/fuelfinance
youtu.be/eI5VH2Ks9o4

Who are we searching for?

We’re looking for an AI Researcher who’s excited to build real AI features used by startup founders every day. You’ll help make our AI Copilot smarter, more accurate, and more helpful - working with modern LLMs, real financial data, and a team that moves fast. If you’re curious, hands-on, and ready to grow, you’ll enjoy this role.

Team structure: 1 Engineering Manager, 2 Senior Full-Stack Developers, 1 Middle Full-Stack Developer, an AI Researcher, and a Head of R&D (responsible for product management and product strategy).

What are your responsibilities?

• Help build and improve our AI Copilot - including many different AI agents that will help our users to work with the product and make decisions
• Create and refine prompts so the AI gives accurate, helpful, and user-friendly answers.
• Set up and improve systems that help the AI remember context during longer conversations and increase the accuracy rate of answers
• Work on making the AI faster and cheaper to run by optimizing latency, token usage, and retrieval quality.
• Integrate modern LLMs (GPT-4, Claude, etc.) into our product with proper error handling and safety checks.
• Use function calling, embeddings, vector search, streaming responses, and async processing to build new AI features.
• Experiment with different AI models and configurations to see what performs best in real scenarios.
• Stay up to date with the latest AI research and apply useful techniques to our product.
• Prototype new AI abilities - such as predictions, automated reasoning, or small autonomous agents.
• Create and maintain datasets and automated tests that check how accurate the AI is across financial use cases.
• Prepare and structure financial data for AI use, and help build data pipelines for RAG (Retrieval-Augmented Generation) systems.

What are the preferred requirements for the role?

Must-have skills:

• 1–2+ years of AI/ML experience (internships, projects, research, or work).
• Solid Python skills and ability to write clean, maintainable code.
• Experience with LLM APIs (OpenAI, Anthropic), embeddings, vector databases, and RAG systems.
• Understanding of prompt engineering fundamentals and LLM limitations.
• Ability to evaluate AI quality using structured datasets, metrics, and experiments.
• Knowledge of basic ML and NLP concepts (supervised learning, embeddings, evaluation metrics).
• Strong problem-solving mindset, fast iteration speed, and high ownership.

• English B2.

   

Nice-to-have skills:

• Experience with LangChain, LlamaIndex, or similar frameworks.
• Familiarity with Pinecone, Weaviate, Chroma, or other vector DBs.
• Knowledge of financial data logic or accounting basics.
• Understanding of AI safety, guardrails, and hallucination mitigation.

• Experience with experimental design, A/B testing, or statistical validation.

   

Reporting Structure

You will report to the Head of R&D and the Engineering Manager.

Recruitment Process:

• Recruiter interview
• Technical interview
• Test task
• Test task review call with the hiring manager (*optional stage)
• Cultural fit interview

Why work with us?

• Build applied AI that powers financial intelligence for global startups.
• Full ownership: what you ship goes directly into production and impacts real customers.
• Learn deep fintech and financial logic - rare, high-value expertise.
• Work directly with senior engineers and founders.
• Move fast, experiment often, and grow into a mid-level AI Researcher role quickly.
• Flexible schedule, 18 days of paid vacation, 10 paid sick days, and a low-ego team culture.

Responsibilities:

• Own and support core ML infrastructure (MLflow, CVAT, GPU/CPU cloud instances, internal data tools).
• Assist Data Engineers with deploying and maintaining data pipelines.
• Act as the primary contact for ML and Data teams on infra-related requests.
• Improve reliability and efficiency by adding automation, monitoring, and tooling enhancements.
   

Must have:

• Knowledge of Python, Terraform, Docker, Linux.
• Hands-on experience with cloud environments (Azure prefered).
• Understanding of the end-to-end ML lifecycle (data → training → evaluation → deployment → monitoring).

Nice to have:

• Familiarity with Kubernetes.
• Experience with FFmpeg or GStreamer for video processing and streaming.
• Experience with model serving frameworks and inference formats (ONNX, TensorRT, OpenVINO, NVIDIA Triton).
• Experience deploying computer vision models, especially to edge/embedded devices (NVIDIA Jetson, Intel platforms, Raspberry Pi).

• Надаємо бронювання від мобілізації

Softcery builds advanced AI systems for B2B SaaS companies. We partner with founders in the US and UK to design, build, and scale production-ready AI solutions that solve real business challenges. Our team focuses on complex AI engineering — systems that are technically robust, business-aligned, and built to scale. We combine deep technical expertise with strong product thinking, helping companies move from AI ambition to real, production impact.
 

Our work splits into two directions: end-to-end AI B2B SaaS platforms for startups and targeted AI solutions for larger product companies. Multi-agent architectures, complex RAG pipelines, voice systems, document intelligence — the kind of work where you’re often the first to solve a specific problem.
 

We are looking for an AI Software Engineer. You’ll build AI systems — client projects, internal R&D, or both. Some work is exploratory: new problems, unclear approaches, figuring things out. Other work is structured delivery: clear scope, defined milestones, ship and iterate.
 

If you think before you build, ask “why?” before “how?”, and can explain complex technical trade-offs to non-technical founders — join us!

 

What You’ll Do:

• Conversational AI — chat agents, voice systems, customer support automation. Prompt engineering, context management, handling edge cases that break naive implementations.
• Document & Data AI — RAG systems, document processing, content generation. Chunking strategies, retrieval optimization, working with messy real-world data.
• Multi-agent systems — orchestrating multiple AI components, agent architectures, workflows where one model’s output feeds another.
• Full-stack integration — connecting AI to existing platforms, APIs, databases. The AI is only useful if it works within the product.
• Direct client collaboration — understanding requirements, presenting solutions, managing expectations.
  
   

What We’re Looking For:

• Excellent knowledge of Python — most of our solutions are built on it.
• Experience building with LLMs, prompt-engineering skills (GPT, Claude, Gemini) — not just calling APIs, but understanding how to make them actually work.
• Familiarity with agent architectures and multi-agent systems — you’ve built or worked with agentic workflows, understand the patterns.
• Experience with SQL DBs — you have a good understanding of data structuring.
• Product mindset — you think not only technically, but also with the user’s needs in mind. Ready to look for the best solutions, not just “get the job done.”
• Fluency in Ukrainian and English (Upper-Intermediate+) — because communicating with customers is part of the job.
  
   

Nice to nave:

• Basic DevOps/MLOps skills.
• Knowledge of JS/TS.
• Experience in consulting or client-facing technical roles.

What We Offer:

• Structured onboarding & dedicated support — you’ll get a clear onboarding plan, documented workflows, and a team that’s got your back.
• Flexible remote schedule — work from wherever and whenever you’re most productive.
• Learning budget — we cover books, courses, English lessons, and AI tools for your professional growth.
• Full accounting support — so you can focus on the work, not the paperwork.
• Time off — 20 paid vacation days, 12 sick days, 2 paid period leave days/month (for women), and your birthday off.
• IT Cluster membership — access to professional events and networking opportunities in the local tech community.

🔁 Hiring Process: Recruiter Interview → Tech Interview → Test Task → Final Interview.

If you care about who you work with, what you create, and how it affects the outcome, we will definitely be on the same page. We’re excited to meet you 👋

About the company

Are you tired of missing important moments in your weekly game because no one recorded you? Say goodbye to FOMO and hello to PUSHIT!

PUSHIT allows you to easily catch up on all the highlights you did while playing your sports game.

Our advanced replay system allows you to capture moments previously taken, so you never have to miss anything.

See those videos for more information about PUSHIT:

1. https://www.youtube.com/watch?v=uQrXgheKjCg
2. https://www.youtube.com/watch?v=pmdihAft2f8

See our current mobile apps:

1. IOS
2. Android

What is the job

You’ll be the Machine Learning Engineer on a compact, fast-moving team, working directly with the founders. Your mission: design, train, and ship computer-vision models that recognize sports events and generate highlight videos—running both in the cloud and on edge devices.

Responsibilities

• Build & improve CV models – object detection, action recognition, semantic segmentation, tracking, and event classification for multi-camera sports footage.
• Optimize for the edge – convert and quantize models (TFLite/ONNX/RT-Core) so they run in real time on Raspberry Pi 5 and ARM-based phones.
• Own the ML pipeline – data collection, labeling guidelines, experiment tracking (Weights & Biases / MLflow), automated training, and CI/CD to Kubernetes.
• Collaborate cross-functionally – work with backend, video-encoding, and mobile teams to integrate inference results into our NestJS APIs and Flutter/Angular clients.
• Raise the bar – research state-of-the-art techniques, run ablation studies, author technical specs, and mentor future student interns.

Requirements

• Strong Python (3 yrs+) and deep-learning expertise with TensorFlow and/or PyTorch.
• Solid background in computer vision: convolutional nets, attention mechanisms, spatio-temporal models (e.g., I3D, SlowFast).
• Experience deploying models to mobile or edge hardware (TFLite, Core ML, TensorRT, or similar).
• Familiarity with Docker & Kubernetes workflows for scalable training/inference.
• Proven ability to turn research into production code: at least one project or product in the wild (GitHub, app store, or academic publication).
• Comfortable with version control, code reviews, agile tickets, and writing clear documentation.
• Passion for sports—or at least enough curiosity to spot a backhand winner or a slam-dunk replay!

• English—professional level (our dev team is global).

   

Bonus points

• Experience with video encoding pipelines (FFmpeg, HLS, RTMP) or real-time streaming protocols.
• Knowledge of AWS/GCP services for training at scale (SageMaker, Bedrock, Vertex AI).
• Skills in data annotation tooling or active-learning strategies to shrink labeling budgets.
• Background in satellite or aerial image segmentation, sign-language or face-recognition projects (great analogies to sports CV challenges).

• Love for open-source: contributions to CV libraries.

   

Why PUSHIT?

• Ship features that thousands of weekend athletes use every day.
• Work on cutting-edge CV problems with real-time performance constraints.
• Small team ⇒ huge ownership, zero bureaucracy.
• Fully remote
• Competitive salary, early equity, and budget for conferences & GPUs.

We are seeking a highly skilled Lead AI Engineer to design, integrate, and optimize AI-driven solutions across our platform. This role will focus on integrating existing AI tools and services, enhancing data processing and analysis workflows with AI, and laying the technical foundation for advanced AI capabilities.

You will work closely with backend, frontend, and product teams, and over time, grow into an AI Lead position, shaping the long-term AI strategy and architecture.

Key Responsibilities

AI Integration & Architecture

• Integrate and orchestrate third-party and in-house AI/ML tools (e.g., LLMs, embeddings, vector databases, AI APIs).
• Design scalable AI-powered services that integrate seamlessly with existing systems.
• Evaluate new AI technologies and tools, and recommend adoption based on business impact.

Data Processing & AI Optimization

• Optimize data pipelines for AI-driven processing, analysis, and automation.
• Apply AI techniques to improve data quality, insights generation, and operational efficiency.
• Collaborate with data and product teams to translate business needs into AI solutions.

Backend & Frontend Collaboration

• Build and maintain AI-enabled backend services using Python, AWS, and RESTful APIs.
• Expose AI capabilities via well-structured APIs for frontend consumption.
• Work with frontend engineers to integrate AI features into React applications.

Scalability, Reliability & Security

• Ensure AI solutions are production-ready, scalable, cost-efficient, and secure.
• Monitor performance, latency, and accuracy of AI systems in production.
• Implement best practices for model versioning, observability, and responsible AI use.

Leadership & Growth

• Act as a technical mentor for engineers working with AI-related features.
• Contribute to defining AI standards, best practices, and long-term roadmap.
• Gradually take ownership of AI architecture and strategy, growing into an AI Lead role.

Required Qualifications

• 5+ years of relevant experience in software engineering, machine learning, or AI-focused roles.
• Strong proficiency in Python, with experience building production backend systems.
• Hands-on experience with AI/ML integration, including LLMs, ML APIs, or AI platforms.
• Experience with AWS (e.g., EC2, Lambda, S3, SageMaker, or similar services).
• Solid understanding of RESTful API design and microservice architectures.
• Experience collaborating with frontend teams using React or similar frameworks.
• Strong knowledge of data processing, analysis pipelines, and performance optimization.
• Ability to design systems that balance experimentation with production reliability.

Nice to Have

• Experience with MLOps, model deployment, and monitoring.
• Familiarity with vector databases, retrieval-augmented generation (RAG), or agent-based systems.
• Experience optimizing AI cost, latency, and inference performance.
• Prior experience mentoring engineers or leading technical initiatives.
• Exposure to AI ethics, governance, and compliance considerations.

What We Offer

• Opportunity to build and scale AI capabilities in a real-world production environment.
• Clear growth path toward an AI Lead position with strategic ownership.
• High level of autonomy and technical influence.
• Collaborative environment working across backend, frontend, and product teams.
• Competitive compensation and benefits, commensurate with experience.

Impressit is looking for an AI Engineer to join a cross-functional product team working on an AI-native EdTech platform focused on workplace skills assessment, personalised coaching, and voice-based practice experiences for young adults.

What do we expect?

— 2–3+ years of commercial experience building production AI/ML systems using LLMs or SLMs
— Strong Python skills with hands-on experience in FastAPI and Pydantic
— Data-driven mindset: experience designing experiments, collecting evaluation data, and iterating based on measured outcomes
— Hands-on experience with Google Cloud Platform, especially Vertex AI
— Experience integrating speech-to-text services (e.g. Google Speech-to-Text, Assembly AI)
— Solid experience with audio processing and vocal analysis
— Experience building AI pipelines for batch inference
— Familiarity with prompt management and AI observability tools (e.g. Langfuse)
— Understanding of evaluation approaches for AI/ML systems
— Experience with SQL databases, particularly PostgreSQL
— Comfortable working with Git and Docker
— Strong problem-solving skills and ability to work autonomously
— Good communicator, comfortable collaborating in cross-functional teams
— Upper-Intermediate or higher level of English

What will you do?

— Build and maintain production AI pipelines for assessment, feedback, and coaching
— Design and iterate on prompt and context engineering for scenario generation and performance evaluation
— Evaluate and select LLMs and SLMs for different AI tasks (transcription, analysis, generation, assessment)
— Develop AI agents and role-playing systems for interactive learning experiences
— Build pipelines for audio processing and transcription analysis
— Implement batch inference workflows for scalable assessment scoring
— Design evaluation frameworks using human-labelled data and quantitative metrics
— Collaborate with product and engineering teams on AI-driven features
— Contribute to AI architecture decisions and long-term technical strategy

As a plus:

— Experience with multi-agent orchestration frameworks (e.g. LangGraph, Google ADK)
— Familiarity with Python-based prototyping tools (e.g. Streamlit)
— Previous experience in EdTech, digital coaching, or learning platforms
— Hands-on experience with audio processing libraries (e.g. librosa)
— Passion for evidence-based AI, system reliability, and end-user quality