Jobs ML / AI

Imagine enhancing an AI assistant that already lives on Macs — one that truly understands its users, adapts to their habits, and helps them stay focused on what matters most. Eney is MacPaw’s AI companion for macOS, designed to organize, automate, and simplify users’ daily workflows.

Now, we’re taking Eney to the next level — making it smarter, faster, and capable of running advanced LLMs directly on-device. As a Senior ML Engineer, you’ll fine-tune and optimize the latest LLMs using cutting-edge techniques (LoRA, Q-LoRA, DPO, GRPO), build scalable ML pipelines, and shape how AI seamlessly integrates into everyday Mac experiences.

In this role, you will:

• Train and fine-tune LLMs (e.g., LLaMA, Gemma, Qwen) for specialized tasks (such as function calling, charting, parameter parsing) and ensure their effective deployment across diverse environments, including on-device (MLX)
• Develop and apply model optimization and compression techniques (e.g., dynamic pruning, quantization) to enable high-performance on-device inference
• Conduct rigorous evaluation and benchmarking of LLMs to measure performance, accuracy, and efficiency across different setups
• Adapt LLMs for domain-specific tasks using techniques such as prompt engineering, adapter-based fine-tuning (PEFT), and multi-modal extensions.

Skills you’ll need to bring:

• Strong background in classical ML and NLP
• Solid knowledge of deep learning, going beyond just LLMs (e.g., CNNs, RNNs, Transformers, Autoencoders)
• Proficiency in Python and deep learning frameworks (e.g., PyTorch)
• Deep experience with LLMs: training large and small models using various techniques (fine-tuning, post-fine-tuning, DPO, GRPO)
• Practical experience with LoRA / Q-LoRA and other adapter-based fine-tuning methods
• Knowledge in model optimization (pruning, quantization), evaluation, and deployment
• Ability to design and automate ML pipelines with a focus on scalability and maintainability
• Upper-intermediate English & fluent Ukrainian

As a plus:

• Experience working with multi-modal data: structured/tabular, images, audio, or video
• Experience in synthetic data generation
• Hands-on experience with LLM production deployment: monitoring, evaluation, and metrics tracking
• Familiarity with on-device ML and performance optimization
• Swift knowledge or interest, as the company’s products operate in the Apple ecosystem
• Background in computer vision, time series, or reinforcement learning

What We Offer:

• We are a Ukrainian company, and we stand with Ukraine against the russian aggression
  We maintain workplaces for the mobilized Macpawians and provide financial support to colleagues or their families affected by the war. Here, you can also read about the MacPaw Foundation, which intends to help save the lives of Ukrainian defenders and provide relief to as many civilians as possible.
• We are committed to our veterans
  Our Veteran Career and Empowerment Program is designed to ensure our veterans and active military personnel receive the recognition, support, and opportunities they deserve.
• Hybrid work model
  Whether to work remotely or at the hub is entirely up to you. If you decide to mix it, our Kyiv office, which works as a coworking space, is open around the clock. The office is supplied with UPS and Starlink for an uninterrupted work process.
• Your health always comes first
  We guarantee medical insurance starting on your first working month. For those abroad, you can receive a yearly Medical insurance allowance as compensation for managing your medical expenses.
• Flexible working hours
  You can choose a schedule that is comfortable for you. No one here tracks your clock in/out because MacPaw is built on trust and cooperation.
• Space to grow both professionally and personally
  Education opportunities to grow both hard and soft skills, annual development reviews, and internal community.
• Teams we are proud of
  We build honest, transparent, and reliable relationships within teams. Every Macpawian can improve processes and implement their ideas. We encourage open and constructive feedback and provide training for Macpawians on giving and receiving feedback.
• Office designed for people (and pets)
  Our office has it all: a spacious workplace with enough room for sitting up, lying down, and running around; a gym for recreation; cozy kitchens; a sleeping/meditation room; and a terrace with a view where we throw summer parties. Also, we have two cats living in the office, and you are welcome to bring your pets to the office (we have separate floors for cats and dogs).
• Time-off policy that covers life’s needs
  Convenient personal time-off policy to help you take care of essential matters in your personal life, and parental leaves. On top of all that, sabbaticals are open after 5 years of being with MacPaw.
• Join social initiatives with MacPawCares
  MacPaw participates in numerous humanitarian aid and charity projects across many fields, and you are welcome to jump in to make the world a better place.
• We’re an equal-opportunity employer. Here is a safe place for applicants of all backgrounds
  We are hiring talented humans. Meaning with all our variety of backgrounds and identities, including service members and veterans, women, members of the LGBTQIA+ community, individuals with disabilities, and other often underrepresented groups. MacPaw does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
  
  *Some benefits are under development, and new adjustments are possible.

We present an engaging opportunity to explore and work with various technologies beyond ChatGPT prompts. You’ll have the flexibility to transition between teams, enabling you to contribute to diverse projects, including complex LLM training pipelines, 3D generative AI, diffusion models, and multimodal edge ML.

Our team comprises experts in the foundational elements of next-generation AI systems, encompassing multimodal inference, generative reasoning, and robust training pipelines. We also maintain an in-house GPU cluster, providing resources for interacting, training, and experimenting with larger models for both professional projects and personal exploration.

Joining our team — means joining a knowledgeable group of researchers and engineers in an environment eager to stay at the forefront of AI innovation, a critical endeavor in today’s rapidly advancing AI landscape.

Requirements:
• Strong Python Experience (1 year +)
• Experience with building Generative AI projects
• Specialized experience with LLMs, LangChain, LangGraph, LangFuse, RAG, and related technologies
• Experience in building REST APIs, knowledge of Docker, relational & vector DBs
• At least upper intermediate written/spoken English
• Be able to visit the office at least 3 times a week

Would be a plus:
• Experience with building Voice-to-Voice AI Systems using LiveKit or similar frameworks
• Knowledge of existing yet fresh AI tools, AI marketplaces, etc.
• Knowledge of various machine learning methodologies, including classic machine learning, recommendation engines, natural language processing, computer vision, and beyond
• C/C++ knowledge
• Experience in edge ML

Key Responsibilities:
• Tackle tough problems and find creative ways to solve them
• Maintain and optimize the solution for maximum speed and flexibility
• Guide, tune, and train LLMs
• Write clean and reusable code
• Improve your skills and stay up-to-date with emerging technologies

What We Offer:
• Startup culture, a strong goal-oriented team, and a research mindset
• Opportunity to leverage your engineering skills for fellow engineers and shape the future of AI
• Working with the newest technical equipment (Latest MacBook Pro)
• 20 working days of annual vacation leave
• English courses, Educational Events & Conferences
• Medical insurance

We are looking for an AI/ML Engineer to help build AI-powered systems using modern LLM architectures.

Responsibilities:

• Design the pipeline from input processing to generation and streaming.
• Implement file processing and context preparation.
• Build semantic search and summarization using embeddings and vector databases.
• Develop structured and hierarchical LLM outputs.
• Design agent architectures (roles, context management, JSON Patch updates).
• Select and implement frameworks such as LangGraph, LangChain, or alternatives.

• Optimize performance, reliability, and error handling.

   

Requirements:

• Strong Python and AI/ML experience.
• Experience with LLMs, RAG pipelines, embeddings, and vector DBs.
• Familiarity with AI orchestration frameworks (LangChain, LangGraph, etc.).
• Understanding of agent-based systems and structured outputs.

• Good English communication.

   

Format: Part-time collaboration, flexible schedule.

What We Offer :

 Professional Growth & Support:

• Mentorship: Hands-on learning from senior experts.
• Career Growth: A clear and documented path to advance.
• Feedback: Continuous support and regular performance reviews.

• Accounting: Full paperwork and tax support managed by us.

   

 Work-Life Balance & Flexibility

• Flexibility: Work from home or our Lviv office (Hybrid).
• Vacation: 18 days of paid annual leave.
• Extra Leave: 10 additional paid days off every year.

• Sick Days: 5 paid days for your health and recovery.

   

 Culture & Office Life

• Office Perks: Free lunches for those working from the office.
• Team Events: Regular gatherings and community-building activities.
• Celebrations: Personal gifts for your work milestones.
• Team Spirit: Corporate gifts and a supportive atmosphere

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

Requirements:

• Experience with Transformer models: BERT, RoBERTa, GPT, T5, LLaMA, Mistral, Falcon, etc.
• Strong knowledge of Python; experience with PyTorch, TensorFlow, and Hugging Face Transformers.
• Understanding of modern LLM architectures and fine-tuning techniques: LoRA, PEFT, Instruction Tuning, RAG.
• Experience with NLP tasks: classification, text generation, machine translation, QA systems, etc.
• Familiarity with evaluation metrics: accuracy, F1, BLEU, perplexity, ROUGE, etc.
• Basic knowledge of statistics and classical machine learning.
• Experience with MLflow, DVC, or similar tools.
• Experience with model containerization (Docker).
• Understanding of CI/CD principles in ML projects.
• Skills in model deployment using FastAPI / Flask / TorchServe / Triton.
• Experience with cloud infrastructure (AWS, GCP, Azure, or local cloud providers).

• Bonus: experience with Kubernetes, Airflow, Kubeflow, Ray.

   

Responsibilities:

• Selecting and configuring modern Transformer/LLM models for company-specific tasks.

Fine-tuning, LoRA tuning, model distillation, and quantization.

• Preparing and processing datasets (including augmentation).
• Deploying models to production and automating pipelines (data → training → inference).
• Monitoring model performance in production, retraining, and optimization.
• Collaborating with Data Engineers and DevOps to build the MLOps infrastructure.

• Evaluating model performance using various metrics and analyzing results to identify areas for improvement and optimization.

   

We offer you:

• Having the capability to create something new and witness your own input.
• You can find confidence in the future here, but rest assured it won't be dull. 
• Join a dynamic and expanding community. Our company is experiencing growth and expanding into Europe. Currently, we have offices in Kyiv, and Warsaw and plan to open additional locations in other countries. 
• Full-time employment contract.
• Multisport (light). 
• Paid vacation, sick leave.

Interested in joining our team? We invite you to submit your CV.

<By submitting your CV to LLC “GigaCloud”, EDRPOU code [39792589] (hereinafter referred to as the “Company”), in response to our vacancy, you consent to the processing of your personal data contained in the CV by the Company in accordance with the Law of Ukraine “On Personal Data Protection”, ISO 27701 Information Privacy Management System, and the provisions of the GDPR>.

About the Role
We’re looking for an innovative ML Engineer to join our AI team and help design, prototype, and operationalize
advanced AI systems, including Retrieval-Augmented Generation (RAG) pipelines, MCP services, and agentic
workflows. You’ll work closely with Python Developers and MLOps Engineers to bring AI-powered features
from concept to production.

Responsibilities

● Design, prototype, and iterate on AI models, RAG pipelines, MCP services, and agentic reasoning
systems.
● Develop AI-powered services using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex,
Haystack, and DSPy.
● Build and optimize prompts for AI-driven tasks like chat, summarization, information extraction, and
decision support.
● Integrate and tune vector databases (e.g., Chroma, FAISS, Pinecone, Qdrant) to optimize vector
search workflows.
● Collaborate with Python Developers to define service interfaces, APIs, and operational
requirements.
● Implement task decomposition, memory management, and tool-use strategies within agentic
systems.
● Monitor AI system performance, operational risks, and prompt evaluation metrics.
● Stay current with emerging AI frameworks, architectures, and best practices in AI observability and
evaluation.

Requirements

● Strong Python development skills with an emphasis on clean, scalable, and modular code.
● Hands-on experience working with LLMs and agent frameworks.
●Solid understanding of RAG architecture, vector search concepts (cosine similarity, MMR, late interaction), and system design.
● Experience building multi-step agentic workflows and reasoning systems.
● Familiarity with AI performance metrics, model drift detection, and operational monitoring.
● Awareness of AI limitations, including latency, hallucination risks, and explainability challenges.
● Experience with DSPy or other prompt optimization tools is a plus.
● A curious, experimental mindset with a passion for testing emerging AI tools and frameworks

Benefits
● Flexible work arrangements (including hybrid mode)
● Great Paid Time Off (PTO) policy
● Comprehensive benefits package
● Competitive salary
● Opportunities for professional growth and development.
● A supportive, dynamic, and inclusive work environment.

Company Overview:
Webxloo, LLC is an international software development company founded in 2005, with headquarters in Florida, USA, and a branch in Ukraine. Our products, including Autoxloo and Simulcast , focus on business automation and real-time systems in the automotive industry. We are expanding and seeking a highly skilled AI & PHP Backend Developer to join our team.
 

Role Overview:
As an AI & PHP Backend Developer at Webxloo, you will play a dual role: designing and implementing AI-based automation solutions while developing and maintaining robust backend systems using PHP. You will collaborate with cross-functional teams to enhance our product offerings, ensure system scalability, and deliver intelligent automation solutions that provide real business value.
 

Key Responsibilities:

• Design, implement, and maintain AI-driven automation workflows to optimize internal and external processes.
• Build intelligent automation using machine learning, LLMs, and low-code/no-code tools such as n8n, Zapier, or Power Automate.
• Integrate AI features into enterprise platforms and software products.
• Develop and maintain backend modules using PHP frameworks such as YII2, Laravel, or Symfony.
• Work with databases including MySQL/MariaDB, MongoDB, Redis, and ensure efficient data management.
• Implement clean, maintainable code following OOP principles, SOLID, DRY, KISS, YAGNI, and PSR standards.
• Collaborate with front-end developers, QA, design, and support teams to deliver high-quality features.
• Monitor, debug, and enhance existing codebases to ensure system reliability, performance, and security.
   

Required Skills & Qualifications:

• 1+ year of experience in AI development, workflow automation, or backend PHP development.
• Solid experience with PHP frameworks (YII2, Laravel, Symfony) and OOP principles.
• Proficiency with MySQL/MariaDB, MongoDB, and caching/message queue systems (Redis, RabbitMQ).
• Experience with RESTful APIs, XML, DOM, CURL, and Regex.
• Familiarity with AI/ML tools, LLMs, and enterprise automation platforms.
• Strong analytical skills and attention to detail.
• English proficiency (intermediate or higher) for technical documentation and collaboration.
• University degree in Computer Science, Engineering, or a related field.
   

Preferred/Advantageous Experience:

• Experience with cloud platforms, Docker, Kubernetes, or serverless architectures.
• Experience in automotive, healthcare, or digital commerce industries.
• Knowledge of frontend frameworks (React, Vue.js) is a plus.
   

What We Offer:

• Competitive salary with regular reviews.
• Standard working schedule with no overtime (9:00 - 18:00, lunch break 13:00 - 14:00).
• Exposure to international projects with various AI and backend development challenges.
• Career growth, skill expansion, and leadership opportunities.
• Collaborative team environment with experienced professionals.
   

Technical Requirements:

• Computer or laptop with at least 16GB of RAM.
• High-speed internet (minimum 20 Mbps).
• Headset and webcam for regular video calls.
   

If you are interested in this opportunity, we encourage you to apply now.

We are a British—Ukrainian air defence tech company building distributed systems across the frontline. We are looking for a Production ML Researcher / Data Engineer to take ownership of the data and ML infrastructure behind our current and future computer vision products.

Our core value is impact for Ukraine: we build technology that makes a real difference on the actual battlefield, not in labs or on paper specs. We operate with a deep-tech mindset, pushing new technologies where engineering rigor truly matters. We value ownership and responsibility—people who execute, deliver, and stand behind the results.

We especially value engineers with strong analytical thinking and proven problem-solving skills — such as participation in mathematical/programming olympiads or experience contributing to open-source projects.
 

Key Responsibilities

• Build production-grade data collection, labeling, and dataset curation pipelines for CV models
• Design workflows for annotation, quality control, and continuous dataset improvement
• Set up model deployment, experiment tracking, versioning, and monitoring
• Support training and inference pipelines in production environments
• Run experiments with different CV models and approaches, evaluate results, and improve system performance

• Help define the architecture and engineering standards for ML infrastructure across product lines

   

  Requirements:

• Strong background in Machine Learning / Computer Vision
• Hands-on experience building data pipelines for ML systems
• Experience organizing labeling workflows and maintaining dataset quality
• Practical knowledge of model deployment, MLOps, and production ML
• Strong Python skills and experience with PyTorch or similar ML frameworks
• Ability to move between research and engineering: experiment, evaluate, deploy, improve
• Strong analytical thinking and solid foundations in linear algebra, probability, and statistics

• English: B2 or higher (working w/ international team members)

   

  Nice to Have

• Experience in DefenseTech, SigInt, or embedded systems
• Understanding of RF-related data or sensor-driven ML systems
• Experience with real-time or low-latency ML pipelines
• Background in active learning, human-in-the-loop labeling, or continuous retraining workflows

• Open-source contributions or strong олимпиадное / competitive programming background

   

  We Offer

• Meaningful and high-impact work in the AIR defense domain
• Practical R&D environment with real autonomy
• Direct influence on technical decisions and the product direction
• Work in an experienced senior engineering team
• Сlear, fast, senior-to-senior communication with a minimum number of team meetings
• Office in the center of Kyiv (available for onsite work when required)
• Full-time position
• Standard business hours; some tasks may require involvement outside the usual schedule (testing, critical updates)

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior AI Engineer to join one of our clients' team. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.
 

Responsibilities

• Refactor a single-agent prototype into a multi-agent architecture (orchestrator + specialized agents).
• Design orchestration logic, agent communication, and state/session management.
• Implement guardrails (prompt-injection protection, output validation).
• Integrate external APIs with resilient error handling.
• Optimize performance and latency (<2–4 seconds).
• Implement monitoring, telemetry, and observability for production systems.
• Collaborate with cross-functional teams to ensure robust API design and integration.

Job requirements

• Strong experience with LLM systems and multi-agent architectures.
• Proficient in Python, including FastAPI, async programming, and Pydantic.
• Experience with function calling and JSON schema outputs.
• Strong API design skills and integration experience.
• Experience in Azure environment: AI Foundry, Key Vault, Managed Identity, monitoring.
• Solid experience in system architecture and production deployment.
• English: conversational; German: A2 comprehension.

Nice to Have:

• MCP certification or relevant Azure certifications.

OTAKOYI is looking for a smart and eager Senior AI Engineer to join our project team. We like challenges and self-development. If you like it too, don’t hesitate, join us!

Our Partner has an advanced, enterprise-grade agentic AI platform that centralizes intelligence, knowledge, and task automation across ecosystem. Built to enhance productivity, orchestrate complex workflows, and provide proactive insights, it is more than a chatbot—it’s an AI-powered front-end for the company's digital transformation. The platform also underpins another application known as Studio AI, for which this role will also be responsible.

This is a pivotal role, responsible for defining and executing the long-term AI strategy, owning system architecture, and providing strong technical direction to evolve the platform. If you have a passion for building transformative AI solutions, excel in strategic thinking, and thrive in taking architectural ownership — this role offers the opportunity to make a lasting impact.
The ideal candidate will bring a unique mix of visionary thinking, deep technical expertise, and hands-on experience, capable of driving Navigator and Studio AI’s next phase of innovation through technical leadership and architectural excellence.
 

Required Skills 

• Deep AI Expertise: Deep knowledge of machine learning techniques, NLP, LLMs, and data-driven AI architectures, with hands-on experience designing and deploying complex AI systems;
• AI Tech Stack: Proficiency with AI development tools and frameworks such as Azure ML, PyTorch, TensorFlow, LangChain, and transformer-based models;
• Cloud Infrastructure: Advanced experience with Azure-based cloud ecosystems and Kubernetes-based orchestration for scalable AI workloads;
• Production-Grade AI Systems: Experience with vector search (e.g., Milvus), real-time APIs, embedded analytics, and third-party integrations (e.g., MS Graph API, Copilot Studio);
• System Design and Architecture: Expertise in designing scalable, secure, and fault-tolerant AI systems, including familiarity with microservices, API management, and real-time data processing;
• Technical Communication: Ability to clearly articulate architectural decisions, technical trade-offs, and AI roadmaps to cross-functional stakeholders;
• Strategic Mindset: Strong analytical and strategic thinking skills, with the foresight to anticipate future AI trends and an understanding of how to apply them to a multi-functional platform like Navigator;
• Upper-Intermediate level of English is mandatory.

Preferred Skills 

• Industry Experience: Experience within a large, matrixed organization,
preferably in technology or a related industry;
• Experience with AI-driven Multi-Modal Systems: Knowledge of systems integrating chat, voice, visual data, and embedded dashboards is a plus;
• Enterprise AI Context: Familiarity with compliance, governance, and scalability considerations in deploying AI in enterprise environments;
• Project Management: Experience with prioritization and execution in agile settings (without direct team ownership).

Responsibilities 

• Vision & Strategy: Develop and continuously refine the long-term vision , driving innovation, user-centricity, and strategic alignment with Company's broader business goals;
• AI & System Architecture: Lead the design and development of AI-driven architecture, ensuring scalability, robustness, and cutting-edge technology integration across ML, NLP, data pipelines, and automation components;
• Cross-Functional Collaboration: Partner closely with stakeholders from product, design, engineering, and business units to ensure Navigator’s roadmap aligns with business needs and delivers tangible value across Company;
• Platform Innovation: Keep Navigator at the forefront of technology by
incorporating emerging trends in agentic AI, multi-modal interfaces, generative AI, and autonomous orchestration;
• Quality & Performance Optimization: Establish benchmarks for platform performance, reliability, and security. Regularly review and refine Navigator’s core systems to ensure peak performance and user satisfaction;
• User Experience Focus: Drive a user-first approach, ensuring that Navigator’s functionality and interface support intuitive and seamless interactions for Company's employees, partners, and customers;
• Vendor & Technology Management: Evaluate and manage strategic relationships with third-party vendors, especially in areas like NLP, Microsoft integrations (e.g., Copilot), and cloud infrastructure (Azure), to leverage the best available technology.

Recruitment process 

1. Pre-screening Interview with Recruiter (up to 45 minutes)
2. Tech Interview (up to 1,5 hour)
3. Client Interview (up to 45 minutes)

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior ML Engineer to join one of our clients' team. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.
 

Responsibilities:

• Build, maintain, and optimize end-to-end MLOps pipelines for machine learning workflows.
• Deploy, monitor, and scale machine learning models in production environments.
• Implement CI/CD pipelines for ML workflows and model lifecycle management.
• Manage and optimize ML infrastructure using Docker, Kubernetes, and cloud platforms.
• Collaborate closely with Data Scientists and Engineering teams to productionize ML models.
• Ensure reliability, monitoring, and performance of ML systems in production.
• Maintain best practices for model versioning, experiment tracking, and reproducibility.

Job requirements

Must-Have:

• Senior-level experience in Machine Learning / MLOps engineering
• Strong programming skills in Python
• Hands-on experience with ML frameworks such as:
  • TensorFlow
  • PyTorch
  • scikit-learn
• Experience with MLOps platforms/tools such as:
  • MLflow
  • Kubeflow
  • TFX or similar
• Experience implementing CI/CD pipelines using tools such as:
  • Jenkins
  • GitLab CI
  • CircleCI
• Strong experience with containerization and orchestration:
  • Docker
  • Kubernetes
• Experience deploying and managing ML solutions on cloud platforms (AWS, GCP, or Azure)
   

Nice to Have:

• Experience with big data technologies such as:
  • Apache Spark
  • Hadoop
  • Kafka
• Experience with data visualization tools:
  • Tableau
  • Power BI

We are looking for a talented AI Engineer to join our growing engineering team and help build intelligent systems powered by modern machine learning and generative AI technologies. You will design, develop, and deploy AI-powered features that enhance products, automate workflows, and deliver data-driven insights. This role is ideal for engineers who enjoy working at the intersection of software engineering, machine learning, and scalable cloud infrastructure.

Details

Location: Remote (Europe)
Employment Type: Full-time / Contract
Start Date: ASAP
Language Requirements: English – Upper-Intermediate or higher

Key Responsibilities

Design and implement AI-powered applications and services.

Develop and deploy machine learning and generative AI models.

Integrate LLM APIs (OpenAI, Anthropic, open-source models) into products and internal tools.

Build data pipelines and systems to support model training and inference workflows.

Optimize model performance, latency, and cost efficiency.

Collaborate with product, engineering, and data teams to translate business needs into AI solutions.

Monitor and maintain AI systems in production environments.

Requirements

3+ years of software engineering experience.

Strong proficiency in Python.

Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.

Experience integrating LLMs or generative AI solutions.

Knowledge of data processing and model deployment workflows.

Familiarity with cloud platforms (AWS, GCP, or Azure).

Strong understanding of software architecture and APIs.

Nice to Have

Experience with LangChain, LlamaIndex, or AI orchestration frameworks.

Knowledge of vector databases (Pinecone, Weaviate, FAISS).

Experience with RAG architectures.

Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).

Experience building AI agents or automation systems.

Requirements

Overall:
Strong knowledge of Python, TensorFlow or PyTorch.
Bachelor's degree in Computer Science (or related field).
Experience with Machine Learning, Gen AI and Computer Vision.
Experience with python web services.
Experience with cloud ML deployment.
Strong understanding of model training, evaluation, and optimization.
Experience with AWS or GCP or Azure

LLM:
Experience with LLAVA or ChatGPT or LLAMA or Gemini.
Fine-tuning open-source LLMs.
Deploying open-source LLMs.
Familiar with agents.

Computer Vision:
Expertise with tracking, keypoint/pose estimation, action recognition, and depth estimation.
Experience in image and video processing using OpenCV.
Hands-on experience with YOLO and Transformer-based architectures for vision tasks.

Will be a plus:
Data Version Control for Big Datasets.
Optimizing models for edge devices.
C++, Java knowledge a plus

Other:
Ability to multi-task, organize, and prioritize work effectively.
Upper Intermediate or higher level of English proficiency.

What We Offer:
- Competitive salary based on experience and skills.
- Flexible working hours and the possibility to work remotely.
- Opportunities for professional growth and career advancement.
- Friendly and collaborative team environment.
- Access to the latest technologies and tools.

 

We are seeking a highly technical Machine Learning Engineer to work onsite with a client team in Kyiv, supporting multiple customers and delivering production-grade ML solutions.

This role has a strong emphasis on ML Ops, model deployment, and computer vision, with additional exposure to Palantir Foundry (pipelines and UI). The successful candidate will be comfortable working independently in environments with uncertain or evolving requirements, while collaborating closely with both onsite and remote teams.

Key Responsibilities:
 

• Design, develop, train, fine-tune, and deploy machine learning models into production environments.
• Build and maintain ML Ops pipelines, including model versioning, deployment, monitoring, and retraining.
• Develop and support computer vision solutions for real-world business use cases.
• Work with structured and unstructured data to deliver scalable ML solutions from PoC → MVP → Production.
• Use Docker to containerize ML workloads and ensure portability and reproducibility.
• Contribute to and maintain Palantir Foundry pipelines and UI components (prior experience strongly preferred; training can be provided).
• Collaborate with cross-functional teams (engineering, product, client stakeholders) both onsite and remotely.
• Clearly communicate technical approaches, trade-offs, and results to non-technical stakeholders.
• Proactively drive progress and decision-making, even when requirements are ambiguous.
• Analyze data to find patterns and create machine learning solutions for challenging business issues
• Understand the AI/ML program journey to formulate relevant high impact business questions that can be answered through data analysis.
   

Required Skills & Experience:
 

• 3+ years of hands-on experience in Machine Learning, including model training, fine-tuning, and deployment, production ML systems
• Strong experience with Docker for ML workloads.
• Proficient with ML Ops concepts (CI/CD for ML, model lifecycle management, monitoring).
• Hands-on experience with PyTorch, TensorFlow, Keras, advanced Python skills (NumPy, Pandas, Scikit-learn, etc.).
• Experience working with cloud platforms (AWS, Azure, or similar).
• Familiarity with SQL for data analysis.
• Ability to work independently and take ownership of delivery.
• Fluency in English (spoken and written).
• Strong interpersonal skills with the ability to translate client requests into technical solutions and explain complex ML topics succinctly to technical and non-technical audiences

Strongly Preferred / Nice to Have:
 

• Prior experience with Palantir Foundry:Data pipelines, Foundry applications / UI
• Experience with computer vision use cases.
• Experience working in agile delivery environments.

We are looking for an experienced AI Solution Architect to lead the design and delivery of scalable AI solutions built on Microsoft Azure. In this role, you will work closely with business stakeholders, customers, and engineering teams to transform complex requirements into robust AI architectures and production-ready solutions.

You will play a key role in defining architecture standards, guiding delivery teams, and supporting pre-sales initiatives in a consulting-driven environment.
 

Key Responsibilities

AI Solution Architecture

• Lead the end-to-end design of AI solutions based on Microsoft Azure
• Translate business and functional requirements into scalable and secure technical architectures
• Design and validate AI architectures including Retrieval-Augmented Generation (RAG) solutions
• Define and enforce architecture standards, best practices, and governance
   

Technical Leadership

• Act as a trusted technical advisor for customers, internal stakeholders, and delivery teams
• Provide technical leadership and quality oversight throughout the delivery lifecycle
• Support pre-sales activities, including solution design, estimations, and technical proposals
   

Solution Design & Delivery

• Design integrations with Azure AI services and enterprise systems
• Create architecture diagrams, solution blueprints, and technical documentation
• Lead development and validation of PoCs and pilot implementations
• Contribute hands-on to coding, testing, and CI/CD pipeline configuration
   

Required Experience & Skills

• Strong experience designing end-to-end AI solutions on Microsoft Azure in a consulting environment
• Proven background in AI solution architecture, including Generative AI and RAG-based architectures
• Hands-on experience with Azure AI services, including:
  • Azure OpenAI
  • Azure AI Search
  • Azure Cognitive Services
• Solid understanding of Azure PaaS services and cloud architecture principles
• Experience creating architecture diagrams, technical blueprints, and solution estimates
• Experience building PoCs and pilot solutions
• Hands-on experience with coding, testing, and CI/CD pipelines
• Strong communication skills and ability to work as a technical advisor for customers and delivery teams
   

Nice to Have

• Experience in a Tech Lead role
• Experience working in factory-mode delivery environments
• Background in enterprise AI transformation projects