Jobs ML / AI Engineer

We are looking for a Founding Engineer to join a fast-growing start-up developing a product for automated lead generation and recruitment outreach.  

Responsibilities: 

- Autonomously architect, prototype, & build the product from the ground up.

- Develop integrations with AI (e.g. Perplexity, OpenAI) & 3rd party API (e.g. CRMs).

- Leverage your prompt engineering skills to maximize the outcome.

- Horizontally work with founders in discussions on business & product topics.

Requirements: 

- 1+ years of experience in a SaaS/startup previously. 

- Senior-level engineer with 5+ years of software development experience. 
- Experience in RAG & AI agents development and prompt engineering.
- API development and integration experience.
- Database design and optimization (SQL).
- Development in cloud infrastructure (AWS/GCP/Azure).
- Patterns for asynchronous task processing (RabbitMQ, SQS, or similar).
- Experience with n8n/make will be a great plus.

- Authentic obsession with giving customers the best.
- Excellent verbal communication skills.

- Excellent English, strong B2 level minimum.

Job details:

• Full-time.
• Fully remote.
• Long-term.
• B2B contract.
• Start date — ideally ASAP / by mid-April.
• Also, you will get founding member equity % in addition to your fixed salary.

What else will you get:

- Learning how a startup grows.

- Direct impact on product and company strategy.

- Deliver value directly to paying B2B clients.

- Opportunity to build and lead a team and department.

- You will work with the most modern toolset (including Cursor in Agent mode).

The hiring process: 

• 45 min pre-screen interview with a recruitment manager
• 15-30 min call with the client
• a technical deep-dive interview, most likely with online coding (conducted by client)
• online call with the team or key team members

Hello!

If technical process organization is your strong side, we should talk ;)

The group of companies MK:group, consisting of the translation company MK:translations and the business localization company Localica.io, is actively integrating AI and LLM technologies into the production of language services to scale the quality, speed, and efficiency of translation and to expand the range of services.

In this regard, we are opening a full-time position for an LLM & AI Engineer who will help build and improve the AI infrastructure for the next generation of localization solutions.

Key Responsibilities

• Research and implement AI/LLM solutions to automate translation and localization processes

• Deploy and optimize open-source LLM and NLP models

• Fine-tune models for specific language pairs, domains, and content types

• Develop AI pipelines for translation, post-editing, and quality evaluation

• Build systems based on LLMs, RAG, and embedding models for working with multilingual content

• Experiment with new open-source AI tools and adapt them to business needs

We are looking for a candidate with

• Experience working with Python and AI/ML tools

• Understanding of LLM architectures, NLP, or machine translation

• Experience working with open-source models (Llama, Mistral, etc.)

• Experience with GPU, inference, and model deployment

• Skills working with vector databases / embeddings / RAG – will be an advantage

• Experience working with Microsoft 365 Copilot / Copilot

• Ability to independently research new technologies and quickly prototype solutions

+++ Will be a plus if you have

• Experience with machine translation or localization tools

• Experience with Hugging Face, LangChain, LlamaIndex

• Experience with model fine-tuning or working with LoRA/PEFT

• Experience with multilingual or cross-lingual NLP

We offer

• Flexible working hours

• Work with modern AI technologies in the language technology field

• Opportunity to build AI solutions from scratch in a production environment

• Work in a stable but dynamic company with international clients

• The opportunity to influence the creation of a new generation of localization products

This role requires at least 2 years of experience with GenAI, not experimental use.

Inception-1 is a product company that creates AI-driven B2C products designed to help people feel more connected and less alone. Our mission is to build meaningful digital experiences that blend technology with empathy — and to prove that technology can be both human and transformative.

We are looking for a creative and technically skilled AI Content Maker to join our team. In this role, you will use generative AI tools to create visual content and help automate content production pipelines. You will work with modern AI technologies to generate images and videos, maintain character consistency, and support both product and marketing needs.

Responsibilities
 

• Create NSFW visual content (images and video) for the platform using ComfyUI
• Build and maintain ComfyUI generation pipelines
• Work with LoRA models and set up generation workflows
• Maintain high quality and visual consistency of characters
• Generate content in both realistic and anime styles
• Create visual assets for platform content, marketing materials, social media, and landing pages
• Support automation of content generation pipelines
• Integrate and work with AI APIs (LLMs, image and video generation tools)
• Rapidly produce content for campaigns and platform needs
• Collaborate closely with product, marketing, and engineering teams

Requirements
 

• Strong ComfyUI skills
• Experience with Stable Diffusion and AI video generation models
• Experience working with LoRA models
• Understanding of AI-based content generation pipelines
• Understanding of NSFW content production specifics
• Ability to rapidly prototype and iterate on creative ideas
• Familiarity with open-source AI tools and workflows
• Portfolio or examples of previous work
• Willingness to complete a test assignment

Nice to Have
 

• Experience integrating LLM APIs
• Experience building automated AI workflows
• Understanding of AI agents or multimodal pipelines
• Knowledge of marketing funnels and content performance

What we offer
 

• Remote work or comfortable offices in Kyiv (Podil)
• Flexible working hours
• Medical insurance (after probation) and online doctor services
• 20 paid vacation days, unlimited sick leave
• Equipment, learning budget, internal lectures
• Sports activities and gym discounts

We are building an AI-driven platform for Project Estimation that helps businesses accurately estimate complex software projects using LLM technologies.

The product is moving from a working prototype to a scalable production system, and we are looking for an expert to help strengthen the AI engine and system performance.
 

Responsibilities

• Optimize LLM chains and system response time
• Implement parallel request processing for multiple users
• Build and refine agent orchestration using LangGraph
• Improve NLP processing of project requirements and estimation accuracy
   

Requirements

• Strong expertise in NLP and LLM systems
• Hands-on experience with LangGraph and multi-agent architectures
• Solid understanding of concurrency, async workflows, and token optimization
• Experience deploying AI solutions to production environments

Nice to have
 

• Experience with Vector Databases and RAG architectures
• Understanding of the Software Development Life Cycle

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the role:
We are looking for a hands-on Sr. Machine Learning / Computer Vision Engineer with strong practical experience in designing, training, evaluating, and improving vision systems for real-world applications. The ideal candidate combines solid theoretical ML/CV fundamentals with an engineering mindset and is comfortable taking ownership of the full pipeline, from data preparation and experimentation to model optimization and deployment.

Responsibilities:
- Design, train, evaluate, and improve machine learning and computer vision models for real-world production use cases
- Build and maintain end-to-end ML pipelines, including data collection support, preprocessing, feature engineering, training, validation, and inference
- Develop solutions across both computer vision and machine learning tasks depending on business needs
- Perform error analysis, diagnose model weaknesses, and drive improvements in accuracy, robustness, and reliability
- Select and justify appropriate methods and model architectures based on dataset characteristics, product constraints, and deployment requirements
- Work with challenging real-world data, including noisy, limited, imbalanced, or weakly labeled datasets
- Collaborate with engineering and product teams to translate business problems into practical ML solutions
- Contribute to production-ready development with a focus on maintainability, reproducibility, and performance

Requirements:
- 3–5+ years of professional experience in Machine Learning / Computer Vision
- Strong senior-level practical expertise in computer vision, machine learning, and applied model development
- Hands-on experience with tasks such as object detection, image classification, anomaly detection, feature-based approaches, or similar
- Solid understanding of classical ML methods, including tree-based models, linear models, feature engineering, model selection, and evaluation
- Strong Python skills and practical experience with PyTorch, OpenCV, and common ML tooling
- Experience building full ML workflows including data preparation, augmentation, preprocessing, training, validation, testing, and deployment handoff
- Strong understanding of model evaluation, debugging, overfitting, generalization, optimization, and experiment-driven improvement
- Ability to write clean, modular, maintainable code and independently own technical solutions
- Strong analytical thinking, engineering maturity, and problem-solving skills

Nice to Have:
- Experience in adjacent ML domains such as time-series, audio, or NLP
- Experience with embedding-based methods, metric learning, retrieval systems, or memory-bank approaches
- Practical experience with model optimization techniques such as quantization, pruning, distillation, or related efficiency-focused approaches
- Experience working with real-world industrial datasets and ambiguous problem formulations
- Knowledge of software engineering best practices, reproducible experimentation, and pipeline design

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the client:
Our client is an IT company that develops technological solutions and products to help companies reach their full potential and meet the needs of their users. The team comprises over 600 specialists in IT and Digital, with solid expertise in various technology stacks necessary for creating complex solutions.

About the role:
We are seeking an experienced Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will design and prototype data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines, design and implement a state-of-the-art evaluation and benchmarking framework to measure and guide model quality, and do end-to-end LLMs training. You will work alongside top AI researchers and engineers, ensuring our models are not only powerful but also aligned with user needs, cultural context, and ethical standards.

Responsibilities:
- Curation of datasets for pre-training, supervised fine-tuning, and alignment
- Research and develop best practices and novel techniques in LLM training and evaluation pipelines.
- Collaborate closely with data engineers, annotators, linguists, and domain experts to scale data processes, define evaluation tasks and collect high-quality feedback.

Requirements:
Education & Experience:
- 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
- An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.
GenAI & NLP Expertise:
- Practical experience with fine-tuning LLMs / VLMs models
- Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
ML & Programming Skills:
- Strong experience with deep learning frameworks such as PyTorch or JAX for building models.
- Ability to write efficient, clean code and debug complex model issues.

Nice-to-have:
Advanced NLP/ML Techniques:
- Applied experience using Reinforcement Learning in NLP / LLM settings
- Prior work on LLM safety, fairness, and bias mitigation.
- Experience generating and curating synthetic datasets for Supervised Fine-Tuning (SFT), including quality control and scaling considerations.
Research & Community:
- Publications in NLP/ML conferences or contributions to open-source NLP projects.
- Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.
MLOps & Infrastructure:
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
- Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.
- Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.
Problem-Solving:
- Innovative mindset with the ability to approach open-ended AI problems creatively.
- Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation

The company offers:
- Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
- Remote onboarding
- We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners
- Health and life insurance
- Wellbeing program and corporate psychologist
- Reimbursement of expenses for Kyivstar mobile communication

Responsibilities:

• Work closely with different departments (Marketing, Sales, HR, Finance, etc.) to understand their workflows and identify opportunities to improve efficiency using AI tools.
• Analyze existing processes and propose automation or AI-assisted solutions.
• Implement AI-powered automations using available tools (LLMs, workflow automation platforms, data tools, etc.).
• Build and maintain internal AI workflows, prompts, and integrations.
• Train and support team members in using AI tools in their daily work.
• Monitor performance of implemented automations and continuously improve them.
• Document AI workflows, best practices, and internal guidelines.
   

Requirements:

• Strong curiosity about AI and automation and motivation to continuously learn.
• Basic understanding of AI tools (e.g. LLMs, automation platforms, data tools) and how they can be applied in business processes.
• Analytical mindset and ability to break down workflows and identify inefficiencies.
• Basic technical skills (e.g. working with APIs, automation tools, spreadsheets, or scripting is a plus).
• Experience in operations, data analysis, product, or technical roles is a plus.
• Ability to communicate with both technical and non-technical teams.
• Problem-solving mindset and willingness to experiment with new tools.
• Self-driven and proactive approach to identifying improvement opportunities.
   

Nice to Have:

• Experience with automation tools (Zapier, Make, n8n, etc.).
• Experience with prompt engineering and LLM-based workflows.
• Basic knowledge of Python, SQL, or data analysis.
• Experience implementing internal tools or process improvements.

We offer:

• Convenient work schedule (8/9/10/11 — 17/18/19/20);
• 21 working days of vacation;
• 10 working days of sick leave;
• Extra days off for birthday, wedding, etc and for public holidays;
• Payment for training;
• Financial and intangible gifts from the company;
• Free communication, the ability to influence processes and implement your ideas;
• Comfortable and easy management, no tyranny.
   

How We Hire:
We’re not here to make you jump through flaming hoops (unless that’s your hobby — in which case, we’ll cheer you on). Our goal is to see if we’re a good match for each other — and to make sure you enjoy the ride.
1. Pre-Screen Call — 30 min
A quick hello with one of our recruiters. We’ll talk about your background, your goals, and what you’re looking for. In return, we’ll tell you more about ABXplay, the role, the team, and answer any burning questions.
2. Hard Skills Interview — 30–60 min
You’ll meet your potential manager. We’ll dive into the real stuff — your future responsibilities, the challenges ahead, and the kind of work you’d actually be doing (no mystery here).
3. The Offer Stage

Workload: full-time/part-time
Location: Israel, Tel Aviv!
Start: in a couple of weeks
English: B2

Company Description
Our company develops advanced AI solutions for life science, pharmaceutical, and biotech organizations. The company helps clients design practical, high-impact AI systems that improve research, development, knowledge management, and business processes. A key focus is building AI Knowledge Libraries that enable companies to structure, connect, and use their organizational knowledge more effectively with AI:

Role Description
This is a remote contract role for an AI Architect. The AI Architect will be responsible for designing and implementing enterprise AI solutions to specific use-cases, with a strong focus on designing AI Knowledge Libraries for companies in the life science, pharmaceutical, and biotech sectors.

Qualifications
Expertise in Architecture and Architectural Design for scalable and efficient AI systemsStrong experience with Microsoft AzureStrong experience with Microsoft 365 Copilot / Copilot StudioExperience designing and implementing enterprise AI solutionsGreat person to discuss on AI strategy, innovation and practical business opportunities

Domain: SaaS
Project: AI strategy product
Client: Germany
Location: Remote (attending events once a quarter across the EU)
Time Zone: CET
Contract: B2B

About US
DevKit is more than just an IT company - we are a team of passionate professionals dedicated to creating cutting-edge solutions. Our employees work on exciting international startups, collaborating with highly skilled teams from around the world. With expertise in software development, design, and engineering, we help bring innovative ideas to life and drive success on a global scale!
Our mission is to connect exciting projects with top-tier professionals. We are committed to creating a dynamic space where innovation thrives, top talent excels, and global teams unite to develop cutting-edge solutions.

About PROJECT
The company is a trailblazing AI-powered SaaS platform, reshaping the landscape of procurement from a tactical function to a strategic business ally that orchestrates seamless value chains. The state-of-the-art solution empowers organizations to independently develop procurement strategies with a flexible framework adaptable to their specific needs and contexts.

Redefining traditional category management, the company’s all-encompassing solution takes it to new heights by harnessing the capabilities of AI, fostering extensive collaboration, and integrating data from diverse sources beyond conventional category taxonomy. At the product, they are driven by a purpose-centered ethos, dedicated to tackling ESG-related challenges, positioning procurement as a catalyst for positive change rather than merely a cost-cutting entity.

The multitude of prestigious awards and recognitions speaks to their leadership in the AI-driven procurement technology landscape, showcasing our unwavering commitment to innovation and excellence.

Main Tech Stack
AI/DS/ML related stack

Requirements

- Have 5+ years of proven industry experience in applying Machine Learning and AI techniques.
- Demonstrate proficiency in Machine Learning principles and generative models, with an understanding of computational limitations and data privacy considerations.
- Showcase expertise in NLP, LLM (3+ years), including prompt engineering, training, fine-tuning, RAG, evaluation, transfer learning techniques, and anomaly detection.
- Possess knowledge of Data Analysis/Processing, Data Visualization, and Storage systems (e.g., Databases, Data Lakes, Data Warehouses).
- Advocate for best coding practices, thorough documentation, rigorous reviews, data integrity, security, and performance optimization, with expertise in the Python ecosystem and popular ML libraries/frameworks, including those tailored for LLM.
- Have experience in Infrastructure management (MLOps/LLMOps, AWS/GCP Clouds, SQL, REST APIs, GitHub), and overseeing end-to-end ML pipelines.
- Demonstrate proficient English communication skills, both verbal and written, with a focus on clarity, openness, and professionalism.

Responsibilities

- AI/DS/ML initiatives organization-wide, overseeing the entire ML lifecycle from conception to execution.
- Drive continuous development of AI/ML functionalities for our SaaS product, prioritizing well-structured, secure, and scalable code, complemented by comprehensive documentation and rigorous testing protocols.
- Initiate the integration of pertinent research findings into our product, particularly in procurement, through experimentation and the creation of solutions like chatbots, forecasts, and decision support systems.
- Utilize your software engineering expertise and business acumen to foster the growth and maintenance of our ML services, guiding all stages of technology development.
- Establish and manage high-quality datasets, alongside developing data pipelines for procurement data processing.
- Collaborate closely with cross-functional teams of software engineers to enact transformative changes within procurement practices.
- Stay informed about the latest advancements in AI/ML technologies and industry best practices, actively contributing insights for continuous improvement.
- Cultivate a culture of learning, knowledge sharing, and team development within our Data Science team.

Will be a plus

- Seize the opportunity to join the team and make meaningful contributions to our engineering excellence within an international team and context.
- Occasional business travel within Europe may be required, averaging once per quarter, alongside team-building company events.
- Join a pioneering AI-driven procurement technology startup, contributing to the creation of innovative solutions that significantly impact enterprise customers.

Benefits

- A long-term role in a stable, fast-growing company
- Flexible working hours with a results-oriented approach
- Competitive salary and benefits package (vacation, sick leave, national holidays)
- Comfortable workspace, corporate events, and team-building
- Continuous learning, professional growth, and skill development

If you're looking for a place to grow, innovate, and make an impact, we'd love to have you on board!

8+ years software engineering experience

3+ years hands-on ML / AI engineering experience

Strong Python (mandatory)

Proven production experience with LLM systems

Deep understanding of:

- RAG architecture

- Embeddings

- Chunking strategies

- Retrieval optimization

Experience with AWS Bedrock

Experience designing tool-calling LLM systems (MCP or equivalent architecture)

Experience integrating external APIs as agent tools

Experience building REST services (FastAPI or similar)

Experience with vector databases (OpenSearch, Pinecone, etc.)

Experience implementing evaluation frameworks for LLM quality

Experience mitigating hallucinations and prompt instability

Strong understanding of:

- Token economics

- Context window constraints

- Cost-performance tradeoffs

Experience integrating with GitHub and JIRA APIs

Production experience beyond notebooks or PoCs

Job Responsibilities

Architect and implement RAG pipelines on AWS Bedrock

Design knowledge ingestion pipelines (JIRA, GitHub, Confluence, S3)

Define chunking, embedding, and retrieval strategies

Design vector storage and retrieval architecture

Architect tool-calling agent systems (MCP or equivalent)

Define when to use:

- Direct API invocation

- Lambda-based tools

- MCP-based tool integration

- Design and implement structured output agents

Implement hallucination mitigation strategies

Build evaluation pipelines for model quality and regression testing

Optimize token usage and latency

Define model routing strategies (cost vs quality)

Implement guardrails and structured validation

Work closely with DevOps to productionize AI services

Mentor AI engineers and define AI engineering standards

Define long-term GenAI roadmap and architecture patterns

Department/Project Description

We are building an AI-driven SDLC automation platform leveraging AWS Bedrock, knowledge bases, domain agents, and tool-based orchestration.
We are looking for a Lead AI Engineer to design and implement the AI architecture, including RAG pipelines, agent systems, tool-calling mechanisms (MCP-style architectures), model evaluation, and guardrails.
This role requires real production GenAI experience, not experimentation.

Trinetix is looking for a skilled AI-Native Engineer.

We are building an AI-native ecosystem that will power both our internal SDLC and the next generation of AI-driven solutions for our clients. Our R&D organization is developing context-aware AI agents, intelligent engineering tools, and graph-based knowledge systems that integrate directly into real development workflows. 

This initiative will reshape how software is planned, built, tested, and evolved—unlocking entirely new capabilities for our teams and our clients’ product engineering organizations. 

Requirements 

• Hands-on experience building RAG systems, vector search, or semantic pipelines. 
• Familiarity with knowledge graphs (Neo4j, RDF, property graphs, graph DBs). 
• Experience working with LLM APIs (OpenAI, Anthropic, Gemini, Llama, etc.). 
• Understanding of embeddings, text processing, chunking strategies, and retrieval optimization. 
• Experience building developer tooling, internal tools, plugins, or automation. 
• Ability to design and prototype systems independently. 

Nice-to-Have 

• Experience building agentic systems (AutoGen, LangGraph, crewAI, smolagents, function-calling agents, etc.). 
• Experience implementing GraphRAG or similar graph-structured retrieval approaches. 
• Familiarity with AI-powered SDLC tools (copilots, code intelligence, static analysis via LLM). 
• Understanding of software architecture and system design. 
• Experience with CI/CD pipelines, DevOps tooling, or platform engineering. 
• Ability to create ontologies or domain data models. 
• Experience working in R&D would be preferable. 

Core Responsibilities 

• Designing the core models and abstractions that will underpin our AI-native engineering ecosystem. 
• Developing intelligent mechanisms to surface the right information at the right time. 
• Creating assistive capabilities that streamline engineering tasks and workflows. 
• Driving innovation in how software teams interact with knowledge, context, and automation. 

• Collaborating across the organization to embed AI into the end-to-end delivery process. 

   

What We Offer 

• Opportunity to build a first-of-its-kind AI-native SDLC environment 
• Chance to influence engineering workflows across the entire company 
• Work within a high-impact, exploratory R&D team 
• Competitive compensation and growth opportunities 
• Full autonomy to prototype, test, and implement ideas 
• Professional training and English/Spanish language classes   
• Comprehensive medical insurance 
• Mental health support 
• Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more 
• Flexible working hours 
• Inclusive and supportive culture 

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.