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

About The Position

Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps and FinOps and GenAI support that drives real results.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We seek an experienced Senior AI Engineer to join our team. You will work hands-on with innovative startups' Data Science and R&D teams and be in charge of various projects. You will develop robust MLOps pipelines, create cutting-edge Generative AI solutions, implement the latest technologies, and ensure the customers’ success by overseeing the project from inception to completion.

📍 Work location - remote from Ukraine

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• Developing backend Generative AI solutions and POCs, utilizing RAG pipelines, agent-based systems, and LLM-powered services
• Taking existing ML or customer-provided code and adapting it for training, fine-tuning, and production deployment using PyTorch
• Developing and optimizing fine-tuning workflows, model evaluation, benchmarking, and inference optimization
• Provision of ML AWS resources and infrastructure primarily using managed and cloud-native services
• Developing ML-oriented CI/CD pipelines using GitHub Actions, Bitbucket, or similar tools
• Deploying Machine Learning models in production and ensuring they are observable and monitorable
• Collaborating with Solution Architects and DevOps teams on scalable and cost-efficient AI infrastructure
• Learning new skills and technologies quickly to stay up to date with rapidly evolving GenAI tools
• Using and writing Terraform libraries for infrastructure deployment
• Maintaining infrastructures and environments of all types, from dev to production
• Security monitoring and administration

Requirements

• Excellent customer-facing skills to understand and address client needs effectively
• Ability to design and implement cloud solutions and to build GenAI pipelines on AWS
• Experience with one or more large language model frameworks like OpenAI SDK, Amazon Bedrock, LangChain, and LlamaIndex
• Fluency in Python, a good understanding of Linux, and mandatory hands-on production experience with PyTorch
• Ability to understand tools used by data scientists and experience with building Generative AI applications beyond notebooks or demos
• Good understanding of supervised and unsupervised learning, and deep learning concepts
• Fluent written and verbal communication skills in English
• Ability to work hands-on, independently, and deliver under real project constraints
• Bachelor’s or Master’s degree in AI-related fields - an advantage
• Working knowledge of some Vector Databases (OpenSearch, Qdrant, Weaviate, LanceDB, etc.) - an advantage
• Experience with Docker and Kubernetes - an advantage
• Experience with Azure or GCP (DevOps/MLOps) for ML or GenAI workloads - an advantage
• ML certification (AWS ML Specialty or similar) - an advantage

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes
• Soft skills training

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognising the value you bring to our team.

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

• 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;
• 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.

   

This is not a coding role. This is a systems-of-systems role. 

If you build things with AI, this posting isn't for you. 

If you build the systems that govern how AI builds things — keep reading.

What This Role Is

LifeChef is a HIPAA-compliant healthcare platform delivering Medically Tailored Meals. Our engineering team builds on a methodology called Enso — a spec-driven, AI-augmented development framework where every feature starts with a specification, gets built with AI assistance, and is validated against defined criteria.

Enso v1 is linear: spec → generate → validate → ship. It works. But it's hitting scaling limits — the document graph grows with every feature, validation complexity compounds, and the process requires increasing human oversight to maintain quality. This is a familiar problem in any AI-assisted workflow that outgrows its initial architecture.

We need someone to take Enso from v1 to v2: a true agentic system where specialized AI agents handle research, specification validation, code generation oversight, quality assurance, and deviation detection — with structured autonomy, clear escalation paths, and human-in-the-loop at defined decision points, not everywhere.

You would partner directly with the CTO (who designed the current methodology and has strong opinions about where it needs to go) to architect, build, and maintain this system. The first 30 days are heavy collaboration — translating vision into working architecture. After that, you own the evolution of the process while the CTO focuses on product and team.

What You'd Actually Build and Maintain

• Agent topology for the development lifecycle: research agents, spec validation agents, code review agents, compliance checking agents, red-team/adversarial agents — each with defined boundaries, confidence thresholds, and escalation triggers
• Spec-to-code reconciliation system: agents that validate whether implemented code actually satisfies the specification, flagging deviations and ambiguities rather than silently passing
• Multi-model orchestration strategy: routing different tasks to different models based on cost, capability, and risk (expensive models for reasoning, cheap models for classification, open-source where it fits)
• Structured output validation: ensuring agent outputs are parseable, auditable, and actionable — not just "LLM said it's fine"
• Governance and escalation framework: what agents decide autonomously vs. what requires human sign-off, circuit breakers for low-confidence situations, audit logging for compliance
• Evolution engine: the system should improve itself — tracking where agents fail, where human overrides happen, and feeding that back into prompt refinement and architecture changes
• Integration with existing CI/CD: the agentic layer hooks into GitHub Actions, automated testing (Vitest), PHI scanning, secret detection, and compliance validation already in the pipeline

This is infrastructure that the development team operates within. You're not shipping product features — you're shipping the machine that makes product development faster, safer, and more consistent.

What We Need From You

Hard requirements:

• You have designed or built at least one agentic system where AI agents operate with structured autonomy — multi-step workflows with validation, error handling, and escalation. Not just API wrappers. Not just chatbots.
• You understand agent topology as a design problem: which agents need to exist, what their boundaries are, how they communicate, how you prevent cascading failures.
• You have hands-on experience with LLM orchestration frameworks (LangChain, CrewAI, AutoGen, custom implementations — the specific tool matters less than the depth of understanding).
• You think in terms of eval frameworks and validation: how do you know if an agent's output is good? How do you measure drift? How do you build confidence scoring that's actually useful?
• You understand multi-model strategies: when to use which model, cost/capability tradeoffs, how to tier your model usage so you're not burning expensive tokens on classification tasks.
• You can work in both Python and TypeScript, or at minimum are comfortable in one and willing to operate in the other. Our product stack is TypeScript-first but agentic tooling often lives in Python.
• Strong written communication. This role involves heavy async documentation of architectural decisions, process design, and system behavior.

What sets you apart:

• Experience with Model Context Protocol (MCP) — building custom MCP servers, tool-use architectures
• Claude Code, Cursor, or similar AI-native development tools as part of your own workflow (you should be using what you're building systems around)
• Experience in healthcare, fintech, or regulated environments where AI outputs must be auditable and compliant
• Understanding of prompt engineering at the systems level — not "write a good prompt" but "design a prompt architecture that's maintainable, versionable, and testable"
• You've thought seriously about adversarial validation — red-team agents, cross-model verification, structured disagreement as a quality signal
• You have opinions about where agentic AI is overhyped and where it genuinely works, and you can defend those opinions with specifics

What we explicitly don't require:

• A portfolio of 50 agentic projects. The field is young. One deep project with real orchestration depth beats ten shallow ones.
• Product development skills. You won't be building UI or shipping user-facing features.
• Healthcare domain expertise. We'll teach you the domain. You teach us the orchestration.

How We Evaluate

1. Screening questions (in your application) — We're looking for specificity and honesty, not keyword density.
2. Architecture conversation with CTO (90 min) — We'll describe our current system, its limitations, and where we want to go. You'll tell us how you'd approach it. This is a two-way design conversation, not a quiz.
3. Small design exercise (async, take-home) — Given a simplified version of our spec validation problem, design an agent topology. We're evaluating how you think about boundaries, failure modes, and escalation — not production-ready code.
4. Trial sprint (60–90 days) — Heavy pairing with CTO in the first 30 days, increasing autonomy after. Defined milestones at 30, 60, and 90 days.

The Team and Context

Small, senior engineering team, primarily Ukraine-based. The CTO (Jay) designed the Enso methodology, has 20+ years of engineering experience across healthcare, threat intelligence, and enterprise platforms, and has built the governance architecture (constitutions, spec-gates, validation layers) that you'd be evolving. He's technical, direct, and has strong opinions — but he's hiring you because he needs a partner in this, not an executor.

The product stack is Next.js 16, React 19, TypeScript, PostgreSQL, AWS serverless (Lambda, CDK, Amplify Gen 2), with Vitest testing, Pino structured logging, and HIPAA compliance enforced in CI. You don't need to know this stack deeply, but you need to understand it well enough to build agentic tooling that integrates with it.

We're building toward autonomous agentic systems for clinical operations — this development process work is the foundation that makes that possible. If the idea of designing the system that governs how an engineering team builds software excites you, this is the role.

How to Apply

Reply with:

• The most complex agentic or LLM orchestration system you've built — what it did, how it was structured, what you learned
• Your honest take on where agentic AI is right now and what's actually hard
• What interests you about building process infrastructure vs. product features

Generic responses get skipped. We know the field is young — we'd rather hear about one deep experience than a list of tools you've touched.

About the role

We are building an AI assistant for the legal domain that will combine:

• Voice AI agents that can call users and collect structured information
• LLM-based workflows for conversation and reasoning
• RAG system for answering questions based on legal documents
• Knowledge base for structured legal information

The system will work with voice calls, documents, and conversational interfaces, helping automate legal workflows and client communication.

Responsibilities

• Design architecture for AI agents and LLM workflows
• Build voice interaction pipelines
• Develop RAG pipelines for document retrieval
• Integrate LLMs with APIs and internal systems
• Work with vector databases and embeddings
• Optimize prompts, latency, and reliability of AI responses

Tech stack (expected)

Strong experience with:

• Python
• LLM APIs (OpenAI / Anthropic)
• RAG systems
• Vector databases

Nice to have:

• LangChain / LangGraph / LlamaIndex
• Twilio / VAPI / Retell
• Speech-to-Text / Text-to-Speech

• FastAPI

   

Ideal candidate

Someone who has already built:

• AI agents
• RAG systems
• conversational AI
• integrations between LLMs and real products

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

OneAcademy is looking for a Video Designer with strong motion design skills and hands-on experience using AI tools for commercial video production. We are building a fast-scaling education brand focused on high-performance digital content, and we need someone who can combine creativity with speed and ownership.

What You’ll Do

• Create short-form video content (Reels, YouTube Shorts, TikTok) using AI-assisted production tools
• Develop static creatives for social media and marketing campaigns
• Optimize video production workflows to improve speed, efficiency, and scalability
• Adapt content to different platforms and formats
• Work within tight deadlines while maintaining quality standards

Hard Skills & Experience

• 2+ years of strong, hands-on experience with Adobe After Effects
• Basic proficiency in Adobe Photoshop
• At least 6 months of practical experience using AI tools for commercial video production (e.g., Kling, VEO, Sora, or similar)
• Experience with prompt engineering and cost optimization of AI tools (tokens / credits management)
• Solid understanding of composition, color correction, and storytelling fundamentals

Soft Skills We Value

• High level of independence and self-management
• Strong sense of responsibility and ownership over tasks and results
• Proactive mindset
• Fast learner, comfortable adapting to new tools and workflows
• Ability to operate in a performance-driven environment

What We’re Looking For

This role is ideal for someone who is not just an executor, but a creator who understands both aesthetics and performance metrics. You should be comfortable experimenting with AI tools, iterating quickly, and continuously improving production efficiency.

If you thrive in a fast-moving, digital-first environment and want to shape the visual language of a growing education brand — we’d love to hear from you.

Why OneAcademy

• Direct ownership over growth of a core educational product
• Opportunity to build a scalable, data-driven education business
• Global product with long-term LTV focus
• High level of autonomy and fast execution
  
  What We Offer
• Ownership of acquisition strategy 
• Work with large budgets and high-scale performance campaigns
• Direct influence on unit economics and growth metrics
• Opportunity to build and shape your own team
• Remote work with flexible schedule
• Work in a fast-growing global prop trading firm
• Performance bonuses and incentives

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 Founding Engineer with deep expertise in Machine Learning and Computer Vision to take full ownership of the architecture and implementation of detection systems for our current and future product lines.

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

• Detection Systems Development: Build and maintain the full lifecycle of ML solutions across the company’s product lines.
• Inference Engineering: Optimize models for real-time operations.
• Backlog Execution & Implementation:
  • Develop RF Classification models (Radio Frequency signals).
  • Improve the accuracy of DoA (Direction of Arrival) algorithms.
  • Implement drone behavior analysis and pilot localization algorithms.
• Best Practices: Define the architecture, tooling, and approaches to build a scalable ML infrastructure from the ground up.

Skills & Requirements

• Strong theoretical background in Linear Algebra, Probability, and Statistics.
• Experience with Computer Vision models: Classification, Object Recognition, and Tracking.
• Python + relevant ML libraries, PyTorch.
• Experience taking models to production (Production ML).
• Hands-on experience with inference engines.
• Ability to build low-latency, real-time detection pipelines.
• Proficiency in C++ and/or CUDA for building high-performance modules.

Nice to Have

• Experience in DefenseTech, SigInt (Signals Intelligence), or Embedded Systems.
• Understanding of Radio Frequency (RF) physics.

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.

We are looking for an AI/ML Engineer to join our outsourcing team, working on projects within the accounting and financial software domain. The role involves contributing to AI/ML solutions that enhance financial process automation, data processing, and analytics.
 

Responsibilities

• Maintain and enhance existing AI/ML solutions used in financial and accounting automation workflows.
• Design, develop, and deploy new AI/ML models to meet project needs and improve operational efficiency.
• Monitor advancements in the AI/ML field, evaluate new techniques, and provide recommendations on potential improvements.
• Analyze infrastructure and model-related costs, propose optimizations, and assist in forecasting costs for new implementations.
• Prepare and present demos and solution overviews to U.S.-based clients.
• Collaborate with cross-functional teams to ensure smooth integration of AI/ML solutions.
• Document models, processes, and system architecture in Confluence to support maintainability and knowledge transfer.
• Participate in model monitoring and performance evaluation to ensure accuracy, reliability, and alignment with business requirements.

Requirements

• 2+ years of experience in AI/ML or a related field.
• Experience building ML models for batch and/or real-time processing, or experience integrating LLM-based solutions.
• Strong knowledge of Python or JavaScript for machine learning and data science.
• Experience with Jupyter Notebooks, NumPy/SciPy, pandas, scikit-learn, TensorFlow/PyTorch, or GPT-model integrations.
• Understanding of NLP and Computer Vision techniques (traditional and deep learning).
• Good understanding of data engineering, database management, and cloud-based ML infrastructure.
• Experience with AWS services (Athena, S3, Lambda, Kinesis, Glue, SageMaker, Data Pipelines, Data Stores).
• Familiarity with CI/CD practices.
• Ability to optimize algorithms for real-time or low-latency environments.
• Strong knowledge of model training, optimization, and selecting the best approaches for specific use cases.
• Experience deploying AI models to production environments is a plus.

What We Offer

• Competitive salary with regular reviews.
• Support for individual entrepreneurs with accounting assistance.
• Fully remote work.
• A clear path for professional development and growth.
• A friendly team environment and engaging team-building activities (online and offline).