Jobs

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

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

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

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

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

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

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:

• Design, build, and deploy GenAI systems using LLMs for real-world applications, including agentic workflows, RAG pipelines, and orchestration logic.
• Implement multi-step reasoning systems using frameworks like LangChain, LangGraph, Strands Agents, CrewAI, and Bedrock Agents.
• Optimize retrieval pipelines with efficient embedding strategies and vector stores such as OpenSearch, PostgreSQL pgvector, Pinecone, and others.
• Rapidly experiment with and integrate new research and GenAI tooling into scalable prototypes and customer-ready solutions.
• Collaborate with cross-functional teams to ship AI-powered features and assist in aligning AI efforts with business goals.

Requirements:

• 3+ years of experience in AI/ML engineering with a track record of building and shipping production-grade AI systems.
• 5+ years of hands-on experience with Python and deep learning frameworks such as PyTorch and HuggingFace Transformers.
• Experience with orchestration frameworks such as LangChain, LangGraph, Strands Agents, CrewAI, and Bedrock Agents.
• Solid understanding of embedding strategies, retrieval optimization, and semantic search using vector stores.
• Experience with AWS services, including Bedrock, SageMaker, Lambda, and other serverless and container-based deployment approaches.
• Familiarity with MLOps practices, including CI/CD for models, monitoring, and reproducibility in cloud-native environments.
• Strong communication skills and the ability to collaborate across product and engineering teams.
• Fluent written and verbal communication skills in English

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.

WHO WE ARE

Respaid unlocks hidden B2B revenue through AI-powered debt collection, done in a respectful way. 20+ people across US & Europe—incl. 10 UA engineers—ship weekly via Linear, GPT-4 agents & full-stack automation. Backed by Y Combinator plus founders of Dropbox & Docker.

WHY THIS WILL EXCITE YOU

• Ship AI that drives revenue — production impact from day one.
• 99.9% uptime, 10–50× dev velocity — obsession with tooling (Cursor, Claude Code, n8n).
• Small, elite team — zero corporate drag, direct access to CEO/CTO.
• Path to Staff / Lead — out-ship, out-learn, own massive scope.

WHAT YOU'LL TACKLE

• Build end-to-end AI features: data scraping → RAG pipelines → automated system sync.
• Craft idempotent, rate-limit-resilient integrations with CRMs & accounting tools.
• Engineer context-rich AI replies and dynamic recovery orchestration.
• Validate & iterate on AI outputs for production-grade accuracy.
• Contribute light DevOps, CI/CD, SRE for 99.9% uptime.

DAY-TO-DAY OWNERSHIP

• Ship code daily (PHP Laravel & Python FastAPI).
• Pair with AI teammates (Cursor, Claude Code) for 10× throughput.
• Review logs/metrics, squash bugs, automate yourself out of toil.
• Collaborate with leadership on roadmap & architecture.

MUST-HAVE SUPER-POWERS

• Proven experience shipping AI-powered production systems (not research).
• Hands-on with RAG pipelines, large-scale scraping, prompt engineering.
• Strong API integration & automation chops.
• Rapid context switching, self-starter, ownership mindset.
• Upper-Interm. English, clear async communication.

NICE TO HAVE

• Multi-tenant SaaS, deliverability optimization, event analytics.
• IaC, CI/CD, light SRE.

PERKS

• Fully remote; flexible hours (core GMT+2/+3 overlap).
• PTO + national holidays + paid birthday off (and your kids'🎂).
• Private health plan, EN/UA language courses.
• Zero red-tape access to CEO & CTO; path to Staff/Lead for top performers.

HOW TO APPLY

Top 1 % receive a paid 2-hour AI coding challenge.
  Pass → 30-min CEO call → offer.

🚀 Ready to build AI that moves the needle? Hit Apply and share one AI workflow you shipped and its ROI.

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of a fast-growing software product company in advanced manufacturing.
• Learn and fulfil your potential in an open, knowledge-driven culture.
• Share in our ambitious vision and make a meaningful difference towards autonomous manufacturing.

Responsibilities: 

• Develop, test, and deploy machine learning models and algorithms for various applications. 
• Design and implement end-to-end AI solutions that integrate with existing systems. 
• Collaborate with data scientists, software engineers, and product teams to understand business needs and translate them into technical requirements. 
• Optimize and scale AI models for performance, accuracy, and sustainability. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field. 
• Proven experience in developing machine learning models and deploying AI solutions. 
• Strong programming skills in languages such as Python, Java, or C++.
• Proficiency with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). 
• Experience with data processing frameworks and tools (e.g., Pandas, NumPy) and familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes) is beneficial. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies.

Role Overview:
Our partner (headquartered in US, New York, NY) is looking for an innovative agent focused engineer to expand product agent back‑end so new automations can be shipped every week.

Responsibilities:

• Design and implement multi-agent orchestration systems, managing agent interactions, control transfers, and task coordination across specialized agents (planner, email analyzer, search, etc.)
• Develop and maintain agent configuration management systems including dynamic Firestore-based configurations, tool assignments, model selection, and prompt engineering for optimal agent performance
• Build and integrate custom tools and workflows for calendar management, memory systems, UI interactions, and email processing pipelines using sequential agent workflows
• Implement and optimize memory and context management including session handling, persistent user memory (Mem0 experience is a plus), and ensuring agents maintain relevant historical context
• Manage real-time agent communication systems including WebSocket connections, multi-modality support (text/audio/image), and background task processing for seamless user experiences
• Write evals and unit tests to ensure consistency 

Qualifications:

• Expert Python development with strong async/await programming patterns, FastAPI integration, experience with Google ADK (Agent Development Kit) framework or equivalent like LangChain, Crew or similar
• Deep understanding of LLM integration and prompt engineering, specifically with Gemini models, including model selection, response optimization, and token management
• Experience with cloud-native architectures including Firestore for configuration management, Google Cloud services integration, and microservices communication patterns
• Proficiency in building and maintaining tool ecosystems including calendar APIs, memory systems, search integrations, and custom function development for agent capabilities
• Strong background in AI/ML workflows including sequential processing, agent orchestration, error handling, performance optimization, and end-to-end testing of AI systems

About us

We’re building an AI copilot for retail crypto investors and traders. The product answers questions, runs research, and proposes next action. We care about clear, useful outputs and fast iteration more than fancy theory.

The role

Own how the model gets from a user request to a trustworthy answer: route the intent, decide what data to fetch, keep prompts tidy, and return structured results the app can use. You’ll collaborate with product to ship small, frequent improvements.

What you’ll do

• Design and refine LLM workflows.
• Collaborate with the team to align AI workflows with intended UX.
• Write and maintain prompts and schemas.
• Make the model decide well (timeframes, windows, what data it needs, when to re-use cached results).
• Build few-shot scenarios so the model can propose actions safely.
• Reduce token/cost/latency by slimming context and reusing recent results.
• Set up simple quality checks.

You might be a fit if you have

• Experience working on at least 1–2 LLM pipelines end-to-end (from planning to integration and iteration).
• Solid Python or TypeScript skills to glue things together and ship small services or scripts.
• A basic understanding of markets, investing, and crypto, and curiosity to learn more.
• Product sense: you like making answers clearer, safer, and cheaper over time.

Nice to have

• Advanced Python experience in backend / ML / data work.
• Deep understanding of markets, trading/crypto, and finance theory.
• Experience integrating external data sources (market data, news, on-chain) and shaping simple evaluation sets.

We are looking for a Senior Data Scientist on behalf of our client – an early-stage Israeli startup revolutionizing the real estate investment space through AI and alternative data. The company is building an intelligent platform that helps investors identify high-return opportunities at the ZIP-code level using predictive analytics, risk modeling, and automated investment strategies.

This is a hands-on role where you’ll work directly with large-scale, unconventional data sources—from mobility signals to social trends—to build models that forecast property values, rental income, and market shifts before they become obvious to the broader market. You’ll collaborate with engineering and product teams to make data science a core driver of the platform’s success.

Key Responsibilities:

• Design and build predictive models for real estate pricing, rent forecasting, and investment potential at the micro-geographic level (ZIP code).

• Analyze and integrate alternative datasets such as location mobility, social indicators, and macroeconomic data to improve model accuracy.

• Develop, train, and validate machine learning models (XGBoost, linear regression, neural networks, time-series forecasting, etc.).

• Work closely with engineers to integrate models into the production environment.

• Build internal dashboards and data visualization tools to help investors make data-backed decisions.

• Contribute to shaping the overall data infrastructure and tooling.

• Collaborate with company leadership to ensure data insights are embedded in key business decisions.

Requirements:

• 5+ years of experience in Data Science, Machine Learning, or AI.

• Strong proficiency in Python (Pandas, NumPy, Jupyter) and data manipulation techniques.

• Solid SQL skills – writing optimized queries, complex joins, aggregations.

• Experience building and deploying supervised machine learning models.

• Knowledge of time-series forecasting and working with real-world, noisy data.

• Ability to communicate complex analytical insights to both technical and non-technical stakeholders.

• English at a high professional level.

Bonus Points For:

• Experience with geospatial data (GeoPandas, PostGIS, Kepler.gl).

• Background in real estate, urban economics, or working with financial/investment data.

• Familiarity with MLOps tools and best practices.

• Startup experience – ability to move fast and iterate with limited resources.

Impulse is a brain training app that helps people keep their brains sharp with bite-sized fun games and logic puzzles. Impulse is the world’s most downloaded app in the Brain Training category with over 100 million downloads. The app is trusted by users worldwide, with a 4.7 rating on the App Store, and has been featured as App of the Day in over 50 countries, including the UK, Canada, and Australia.

Impulse is a part of Headway Inc, a global tech company that revolutionises lifelong learning by creating digital products for over 150 million users worldwide. Our mission is to help people grow. We’re proud to be ranked 4th among the World’s Top EdTech Сompanies by TIME magazine.

The core of our achievements is our team. That’s why, together with Tetiana, Creative & Production Lead at Impulse, we’re looking for a Junior Creative AI Specialist to join our team of superstars.
 

This job is perfect for you if you want to:

• Work alongside a team of energetic, like-minded experts. You’ll brainstorm, test ideas, and share knowledge across departments — all shoulder to shoulder with people who love what they do.
• Dive deeper into the world of creative marketing and grow fast in this field. This role is just your starting point
• Make a real impact on the performance of a #1 product in its niche. You’ll come up with creative ideas and actually see the difference your work makes.

What you will do:

• Create attention-grabbing visuals, copy, and videos with AI tools.
• Staying on top of the latest AI tools for marketing and creatives.
• Share AI tips and tricks with the team.
• Create a prompt base and applying prompt engineering for the best results from AI.
• Automate routine tasks and put the boring stuff on autopilot — from refreshes and variations to copy, voiceovers, and beyond.

What do you need to join us:

• English at Upper-intermediate level or higher.
• Hands-on experience with core AI tools such as ChatGPT and Sora.
• A passion for discovering what’s possible with AI.
• A perfect mix of creativity and analytical skills.
• Willingness and motivation to learn and grow fast.
• Interest in tracking content trends and best-performing ad practices on social media.
• A logical and structured approach to tasks, and openness to discussing ideas.
• Alignment with the values of our team (more about us - here).

Will be a plus:

• Holding a certificate proving English language proficiency (e.g., IELTS, TOEFL, etc.)
• Experience with market research and competitor analysis tools (AppMagic, FB Ad Library, TikTok Creative Center).
• Good understanding of marketing metrics and the marketing funnel.
• Basic Figma skills.
• Copywriting chops.

What do we offer:

• Work within an ambitious team on a socially impactful education product.
• An office with a reliable shelter, generators, satellite internet, and other amenities.
• Access to our corporate knowledge base and professional communities.
• Personal development plan.
• Compensation for English language learning, external training, and courses.
• Medical insurance and full sick leave compensation.
• Sports activities: running, yoga, boxing, and more.
• Corporate holidays.
• Supporting initiatives that help Ukraine. Find out more about our projects here.

Working schedule

This is a full-time position with a hybrid option. It means that we will prefer you to attend office 2-3 times per week.

Are you interested?
Send your CV!

About the Role:

We are launching a new strategic business unit focused on AI Agent Management Services, combining internal infrastructure development with external delivery of cutting-edge generative AI solutions for enterprise clients.
This is a foundational leadership role responsible for defining the vision, building the business from the ground up, and ensuring sustainable growth through innovation, delivery excellence, and commercial performance.

Key Responsibilities:

Business Unit Leadership:

• Design and establish the AI Agent Services business unit, including team structure, operational model, and key processes.
• Develop and own the strategic roadmap for service development, internal capabilities, and external market expansion.
• Build and continuously refine the portfolio of offerings (consulting, outsourcing, managed services, packaged products).
• Develop and manage the pricing strategy, including value-based pricing models, rate cards, and cost analysis.
• Take full P&L responsibility for the unit: budgeting, forecasting, and ensuring profitability.
• Set and achieve financial targets, including revenue quotas, margin goals, and customer acquisition KPIs.

Service Development & Infrastructure:

• Lead the design and development of AI agent architecture, lifecycle processes, and reusable internal components.
• Establish in-house tools, platforms, and reusable modules to support agent development, integration, testing, and monitoring.
• Ensure all offerings align with responsible AI practices, regulatory compliance, and enterprise-grade delivery standards.

Team & Capability Building:

• Recruit and lead a multidisciplinary team (AI engineers, prompt engineers, delivery managers, solution architects, sales support).
• Foster a culture of innovation, agility, and customer-centric delivery.
• Define and implement performance management and continuous improvement processes for the unit.

Go-to-Market & Business Development:

• Personally drive business development efforts during the initial phase — identifying opportunities, engaging clients, creating proposals, and closing deals.
• Work closely with the marketing team to position the service line, define ICPs, and create compelling sales collateral.
• Act as the face of the AI Agent Services offering, building thought leadership through events, webinars, and content.
• Develop channel and partner strategies (e.g., alliances with LLM providers, platform vendors, or system integrators).

Client Delivery Oversight:

• Ensure high-quality, scalable delivery of AI Agent solutions to clients across industries.
• Support solution architecture and custom offering design for strategic clients.
• Define and monitor SLAs, KPIs, and delivery governance models.

Requirements:

Experience:

• 7+ years in technology leadership or digital transformation roles, with at least 2–3 years in AI/ML solution development or automation service lines.
• Experience building or scaling new service lines or business units in IT, consulting, or AI environments.
• Demonstrated success in owning P&L, hitting revenue targets, and managing business operations.
• Hands-on experience with enterprise client delivery — particularly in consulting, managed services, or outsourcing.

Skills & Competencies:

• Strong knowledge of Generative AI technologies (LLMs, agents, orchestration frameworks like LangChain, vector stores, RAG, etc.).
• Business acumen and ability to design commercial models, pricing structures, and scalable service portfolios.
• Outstanding leadership and communication skills, capable of influencing both technical and non-technical stakeholders.
• Entrepreneurial mindset — comfortable with ambiguity, resourcefulness, and building from scratch.
• Fluent English is required; additional languages (e.g., Arabic, Italian, German, French) are a plus.

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• MBA or equivalent business leadership training preferred.

The role

As the Senior ML Engineer at HelloBiome, you will spearhead our efforts to integrate advanced AI capabilities through machine learning models into our microbiome-based health solutions. In this pivotal role, you will lead a cross-functional team to innovate and enhance our AI-driven platforms, ensuring they are scalable, robust, and aligned with our strategic business goals. Your expertise will guide the development and implementation of machine learning models that power predictive analytics, personalized care, and medical image analysis, crucial for advancing consumer health technologies.

Collaborating closely with biologists, data scientists, and software engineers, you will translate complex business needs into functional and non-functional requirements, ensuring our technology roadmap continuously evolves to meet the dynamic demands of the industry. By establishing robust governance frameworks, you will oversee the lifecycle management of AI models, maintaining high standards of data integrity and compliance with global regulations.

This role includes a competitive cash salary and equity package. Compensation is calculated based on the location of the team member, reflecting HelloBiome’s commitment to fair and equitable remuneration.

Requirements

• 10+ years of experience in the development and deployment of machine learning solutions at scale
• Strong communication and presentation skills to effectively collaborate with various stakeholders
• Proven track record and hands-on experience in software development
• Proven ability to lead and manage projects with cross-functional teams
• Extensive experience in building complex, load-ready ETL and ELT processes using various architectures (n-tier, monolith, microservices, etc.), hybrid stacks (Python, Node.js) and tools
• Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud
• Excellent understanding of machine learning algorithms and techniques including supervised learning, clustering, classification, and recommendation systems
• In-depth understanding of statistical methods and principles underlying machine learning algorithms, including hypothesis testing, probability theory, regression analysis, and Bayesian inference
• Experience with ethical AI practices and ensuring compliance with data protection regulations in the USA and EU
• Experience with healthcare data (e.g., electronic health records, medical imaging data, genomics data) is desirable
• Familiarity with data governance principles and best practices, including data quality management, metadata management, and data lineage tracking for model traceability and accountability
• Experience in driving innovation and thought leadership in research, contributing to publications, patents, or industry conferences is desirable

Responsibilities

• As a Senior ML Engineer, you’ll lead HelloBiome in advancing as a data-first organization, integrating AI into the existing systems, building new ones, and preparing the HelloBiome platform for scaling. You will report directly to the CTO.
• Collaborate with stakeholders to understand business goals and translate them into functional and non-functional requirements
• Build and constantly align technology roadmap with business strategies and their KPIs
• Develop and implement machine-learning models and algorithms for microbiome applications, including medical image analysis, predictive analytics, personalized care, and recommendation systems
• Collaborate with biologists and software engineers to gather requirements, design solutions, and integrate machine-learning models into the HelloBiome platform
• Evaluate and validate models using appropriate metrics and techniques to ensure accuracy, reliability, and robustness
• Optimize machine learning algorithms for performance, scalability, and real-time processing
• Lead the establishment and maintenance of robust governance frameworks for product development and deployment, including model lifecycle management, risk assessment, technology vendor management, and compliance monitoring
• Ensure that data acquisition and processing activities comply with ethical standards and industry regulations
   

About HelloBiome

HelloBiome is an innovative B2B biotech startup at the forefront of AI-powered microbiome innovation. We are dedicated to revolutionizing consumer health by leveraging the microbiome. Through democratizing access to microbiome data, HelloBiome utilizes advanced AI technologies to develop targeted health solutions, transforming these insights into commercial applications for our business clients. Trusted by over 20 clients, including industry giants like Unilever, we are not just predicting the future of consumer health; we are actively shaping it. At HelloBiome, every step we take is towards a healthier future, optimizing well-being one microbiome at a time.

Our Culture

At HelloBiome, we thrive in a globally connected, remote work environment with team members distributed across Europe, the US, Canada, and Korea. Our headquarters are in San Francisco and Our dynamic and international team embodies a culture of kindness paired with a drive for innovation and excellence. We value proactive individuals who bring a self-starter mindset to their roles, always seeking new ways to advance our mission. Attention to detail is crucial in our work, as we are committed to delivering precise and impactful health solutions to our B2B clients.

This remote and flexible work structure not only fosters a diverse and inclusive atmosphere but also encourages a balance between personal growth and professional excellence. Join us and be part of a team that is shaping the future of consumer health through groundbreaking AI-powered microbiome innovation.

Your expertise:

• High personal interest in quantitative and algorithmic approaches
• Knowledge in quantitative analysis, statistics, time-series analysis, ML modeling and forecasting for markets
• Experience from 2 years with Data Science activities, including data research and analysis, algorithmic strategy prototyping and backtesting
• Experience with creating and supporting algorithmic strategies, including their risk management
• Experience in systematically monitoring and evaluating the performance of algorithmic strategies with a set of KPIs

• Experience with SQL, Pandas / NumPy / SciPy, and backtesting frameworks

   

Will definitely be a plus:

• Experience with effectively managing delta-neutral and grid strategies
• Experience in the management of a portfolio of algorithmic strategies
• Experience with data science for Agentic AI and Machine Learning
• Experience in the DeFi, DeFAI, or market-making

• Good knowledge of Finance for markets

   

What’s in it for you?

• Opportunity to deal with top-notch technologies and approaches in a world-leader product company with millions of customers
• Opportunity to make a difference for online privacy, freedom of speech, and net neutrality
• Decent market rate compensation depending on experience and skills
• Developed corporate culture: no micromanagement, culture based on principles of truth, trust, and transparency
• Support of personal and professional development
  • coverage of costs of external trainings, conferences, professional literature
  • support of experienced colleagues
  • in-house events and trainings
  • regular knowledge sharing in teams
  • English classes and speaking clubs
• Life-balance support
  • 25 working days of vacation
  • 5 days of paid sick leave per year without providing a medical certificate (no limitation on sick leaves with medical confirmation)
  • generous maternity / paternity leave program

• Professionally strong environment, friendly and open atmosphere, ability to influence the product development and recognition for it

   

You will be involved into:

• Lead Data Science activities for algorithmic strategies: data research and analysis, prototyping and backtesting, live strategy performance monitoring, designing data pipelines, designing and implementing risk management strategy
• Participate in the full lifecycle of algorithmic strategy development: ideation, data research, strategy design and prototyping, backtesting, implementation, and live monitoring
• Systematically monitor and analyze strategy performance metrics, research and generate hypotheses for improvement, and iteratively test hypotheses

• Define requirements for implementation by Developers of algorithmic strategies and their data pipelines

   

About the company and project:

ZONE3000 is proud to represent its partnership with Namecheap (www.namecheap.com). Namecheap has been on the market for 20+ years and is the 2nd largest domain registry‬ in the world. We are the Namecheap Machine Learning Team.‬

The team prototypes and develops innovative systems with AI and Machine Learning.‬ Currently, there are more than 10 Production systems in the areas of Email, Payments, Customer Service, and Analytics. Some of them have proven quality at the level of global‬ market leaders.‬

The team provides all the conditions for active professional growth. The culture combines‬ the best from enterprises and startups: a high level of professionalism, truly innovative‬ technologies, friendliness, and stability.‬

About the Client and Product:
Our client provides one of the world’s leading online video platforms, designed to power live streaming, online presentations, virtual conferences, events, tutorials, and training sessions. Leveraging advanced browser-based video capture technologies, the platform supports thousands of simultaneous viewers during live events.

Built with state-of-the-art video pipeline technologies—similar to those used by leading organizations like Amazon Video and Netflix—the platform encodes and streams millions of minutes of video content annually, making it a key player in the digital video space.

About the Role:
We are looking for a GenAI Engineer to design, develop, and deploy generative AI solutions. You will work with product teams to integrate AI capabilities, improve automation, and enhance user experiences.

Responsibilities:

• Build, fine-tune, and deploy AI models and pipelines.
• Design scalable AI solutions for text, code, image, or multi-modal generation.
• Evaluate and optimize model performance.
• Collaborate with cross-functional teams on AI integration.

• Mentor junior engineers and share best practices.

   

Requirements:

• 3–7 years of software engineering experience.
• Hands-on experience with AI/ML models, including generative AI.
• Strong software design and problem-solving skills.
• Clear communication and teamwork abilities.

• Upper-Intermediate English or higher. 

   

Preferred:

• Experience with chatbots, content generation, or AI assistants.

• Familiarity with LLMs, embeddings, or retrieval-augmented generation.

   

We Gladly Offer:

• Work in a flexible, Agile, multinational team where innovation and collaboration drive success.
• An opportunity to leverage your skills and experience to build state-of-the-art software products while expanding your expertise in cutting-edge technologies.
• Access to training and continuous learning opportunities to grow your skill set and stay ahead in the evolving tech landscape.
• The chance to work with leading global clients across industries and gain domain expertise in AWS and cloud-based solutions.
• A modern office located in the city center, providing a dynamic and inspiring workspace.
• Flexibility to work both remotely and on-site, allowing you to balance professional and personal commitments effectively.

Help us push AI further — and faster

LoopMe’s Data Science team builds production AI that powers real-time decisions for campaigns seen by hundreds of millions of people every day. We process billions of data points daily — and we don’t just re-apply old tricks. We design and deploy genuinely novel machine learning systems, from idea to prototype to production.

You’ll join a high-trust team that has a 5-star Glassdoor rating led by Leonard Newnham, where your work moves fast, ships to production, and makes measurable impact.

What you’ll do:

• Design, build, and run large-scale ML pipelines that process terabytes of data
• Apply a mix of supervised learning, custom algorithms, and statistical modelling to real-world problems
• Ship production-grade Python code that’s clear, documented, and tested
• Work in small, agile squads (3–4 people) with DS, ML, and engineering peers
• Partner with product and engineering to take models from idea → production → impact
• Work with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse and more

What you bring:

• Bachelor’s degree in Computer Science, Maths, Engineering, Physics or similar (MSc/PhD a plus)
• 4+ years’ commercial Python experience
• Track record building ML pipelines that handle large-scale data
• Excellent communication skills — comfortable working across time zones
• A curious, scientific mindset — you ask “why?” and prove the answer

Bonus if you have:

• Experience with adtech or real-time bidding
• Agile / Scrum experience
• Knowledge of high-availability infrastructure (ElasticSearch, Kafka, ClickHouse)
• Airflow expertise

About the Data Science Team:

We’re 17 ML engineers, data scientists, and data engineers, distributed across London, Poland, and Ukraine — acting as one team, not a satellite office.

What sets us apart:

• Led by an experienced Chief Data Scientist who codes, leads, and listens
• Inclusive, supportive culture where ideas are heard and people stay
• Strong values: open communication, continual innovation, fair treatment, and high standards
• Track record of publishing award-winning research in automated bidding

Don’t just take our word for it — check our Glassdoor reviews (search “Data Scientist”) for a real view of the culture.

About LoopMe:

LoopMe was founded to close the loop on brand advertising. Our platform combines AI, mobile data, and attribution to deliver measurable brand outcomes — from purchase intent to foot traffic. Founded in 2012, we now have offices in New York, London, Chicago, LA, Dnipro, Singapore, Beijing, Dubai and more.

What we offer:

• Competitive salary + bonus
• Billions of real-world data points to work with daily
• Flexible remote/hybrid options
• Learning budget and career growth support
• Friendly, transparent culture with strong leadership

Hiring process:

1. Intro with Talent Partner
2. 30-min technical interview with Chief Data Scientist
3. Panel with 2 team members (technical, culture & collaboration)
4. Offer – usually within 48 hours of final round

Are you ready to design and deploy AI systems that run at truly massive scale?

We are hiring an MLOps Engineer specializing in Large Language Model (LLM) infrastructure to design and maintain the robust platform on which our AI models are developed, deployed, and monitored. As an MLOps Engineer, you will build the backbone of our machine learning operations — from scalable training pipelines to reliable deployment systems — ensuring that our NLP models (including LLMs) can be trained on large datasets and served to end-users efficiently. This role sits at the intersection of software engineering, DevOps, and machine learning, and is crucial for accelerating our R&D in the Ukrainian LLM project. You’ll work closely with data scientists and software engineers to implement best-in-class infrastructure and workflows for the continuous delivery of AI innovations.

What you will do

• Design and implement modern, scalable ML infrastructure (cloud-native or on-premises) to support both experimentation and production deployment of NLP/LLM models. This includes setting up systems for distributed model training (leveraging GPUs or TPUs across multiple nodes) and high-throughput model serving (APIs, microservices).
• Develop end-to-end pipelines for model training, validation, and deployment. Automate the ML workflow from data ingestion and feature processing to model training and evaluation, using technologies like Docker and CI/CD pipelines to ensure reproducibility and reliability.
• Collaborate with Data Scientists and ML Engineers to design MLOps solutions that meet model performance and latency requirements. Architect deployment patterns (batch, real-time, streaming inference) are appropriate for various use-cases (e.g., a real-time chatbot vs. offline analysis).
• Implement and uphold best practices in MLOps, including automated testing of ML code, continuous integration/continuous deployment for model updates, and rigorous version control for code, data, and model artifacts. Ensure every model and dataset is properly versioned and reproducible.
• Set up monitoring and alerting for deployed models and data pipelines. Use tools to track model performance (latency, throughput) and accuracy drift in production. Implement logging and observability frameworks to quickly detect anomalies or degradations in model outputs.
• Manage and optimize our Kubernetes-based deployment environments. Containerize ML services and use orchestration (Kubernetes, Docker Swarm or similar) to scale model serving infrastructure. Handle cluster provisioning, health, and upgrades, possibly using Helm charts for managing LLM services.
• Maintain infrastructure-as-code (e.g., Terraform, Ansible) for provisioning cloud resources and ML infrastructure, enabling reproducible and auditable changes to the environment. Ensure our infrastructure is scalable, cost-effective, and secure.
• Perform code reviews and guide other engineers (both MLOps and ML developers) on building efficient and maintainable pipelines. Troubleshoot issues across the ML lifecycle, from data processing bottlenecks to model deployment failures, and continuously improve system robustness.

Qualifications and experience needed

Experience & Background:

• 4+ years of experience in DevOps, MLOps, or ML Infrastructure roles
• Strong foundation in software engineering and DevOps principles as they apply to machine learning
• A bachelor’s or Master’s in Computer Science, Engineering, or a related field is preferred

Cloud & Infrastructure:

• Extensive experience with cloud platforms (AWS, GCP, or Azure) and designing cloud-native applications for ML
• Comfortable using cloud services for compute (EC2, GCP Compute, Azure VMs), storage (S3, Cloud Storage), container registry, and serverless components where appropriate
• Experience managing infrastructure with Infrastructure-as-Code tools like Terraform or CloudFormation

Containerization & Orchestration:

• Proficiency in container technologies (Docker) and orchestration with Kubernetes
• Ability to deploy, scale, and manage complex applications on Kubernetes clusters; experience with tools like Helm for Kubernetes package management
• Knowledge of container security and networking basics in distributed systems

CI/CD & Automation:

• Strong experience implementing CI/CD pipelines for ML projects
• Familiar with tools like Jenkins, GitLab CI, or GitHub Actions for automating testing and deployment of ML code and models
• Experience with specialized ML CI/CD (e.g., TensorFlow Extended TFX, MLflow for model deployment) and GitOps workflows (Argo CD) is a plus

Programming & Scripting:

• Strong coding skills in Python, with experience in writing pipelines or automation scripts related to ML tasks
• Familiarity with shell scripting and one or more general-purpose languages (Go, Java, or C++) for infrastructure tooling
• Ability to debug and optimize code for performance (both in data pipelines and in model inference code)

ML Pipeline Knowledge:

• Solid understanding of the machine learning lifecycle and tools
• Experience building or maintaining ML pipelines, possibly using frameworks like Kubeflow, Airflow, or custom solutions
• Knowledge of model serving frameworks (TensorFlow Serving, TorchServe, NVIDIA Triton, or custom Flask/FastAPI servers for ML)

Monitoring & Reliability:

• Experience setting up monitoring for applications and models (using Prometheus, Grafana, CloudWatch, or similar) and implementing alerting for anomalies
• Understanding of model performance metrics and how to track them in production (e.g., accuracy on a validation stream, response latency)
• Familiarity with concepts of A/B testing or canary deployments for model updates in production

Security & Compliance:

• Basic understanding of security best practices in ML deployments, including data encryption, access control, and dealing with sensitive data in compliance with regulations
• Experience implementing authentication/authorization for model endpoints and ensuring infrastructure complies with organizational security policies

Team Collaboration:

• Excellent collaboration skills to work with cross-functional teams
• Experience interacting with data scientists to translate model requirements into scalable infrastructure
• Strong documentation habits for outlining system designs, runbooks for operations, and lessons learned

A plus would be

LLM/AI Domain Experience:

• Previous experience deploying or fine-tuning large language models or other large-scale deep learning models in production
• Knowledge of specialized optimizations for LLMs (such as model parallelism, quantization techniques like 8-bit or 4-bit quantization, and use of libraries like DeepSpeed or Hugging Face Accelerate for efficient training) will be highly regarded

Distributed Computing:

• Experience with distributed computing frameworks such as Ray for scaling up model training across multiple nodes
• Familiarity with big data processing (Spark, Hadoop) and streaming data (Kafka, Flink) to support feeding data into ML systems in real time

Data Engineering Tools:

• Some experience with data pipeline and ETL
• Knowledge of tools like Apache Airflow, Kafka, or dbt, and how they integrate into ML pipelines
• Understanding of data warehousing concepts (Snowflake, BigQuery) and how processed data is used for model training

Versioning & Experiment Tracking:

• Experience with ML experiment tracking and model registry tools (e.g., MLflow, Weights & Biases, DVC)
• Ensuring that every model version and experiment is logged and reproducible for auditing and improvement cycles

Vector Databases & Retrieval:

• Familiarity with vector databases (Pinecone, Weaviate, FAISS) and retrieval systems used in conjunction with LLMs for augmented generation is a plus

High-Performance Computing:

• Exposure to HPC environments or on-prem GPU clusters for training large models
• Understanding of how to maximize GPU utilization, manage job scheduling (with tools like Slurm or Kubernetes operators for ML), and profile model performance to remove bottlenecks

Continuous Learning:

• Up-to-date with the latest developments in MLOps and LLMOps (Large Model Ops)
• Active interest in new tools or frameworks in the MLOps ecosystem (e.g., model optimization libraries, new orchestration tools) and a drive to evaluate and introduce them to improve our processes

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
• Remote onboarding
• Performance bonuses
• 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

About Bitmedia Labs
Bitmedia Labs — an international product IT company, has been in the industry since 2014, effectively functioning on a worldwide scale with a crew of 130+ ambitious and highly skilled professionals, creating successful projects in domains such as online advertising systems for the crypto space, blockchain games, and NFT products.

Required Qualifications:

• 2+ years of experience with Python programming and software development;
• Hands-on experience working with LLM models and APIs (OpenAI, Claude, Gemini, LLaMA, etc.);
• Practical knowledge of AI/ML libraries and frameworks (LangChain, Hugging Face, PyTorch, TensorFlow);
• Experience with vector databases (Pinecone, Weaviate, Qdrant, etc.) and embeddings;
• Demonstrated expertise in prompt engineering techniques and best practices;
• Basic experience with model fine-tuning and training pipelines;
• Strong SQL skills and experience with relational/NoSQL databases;
• Proven experience building APIs and backend services (RESTful APIs, background workers, task queues, data processing services) and understanding of application architecture and system design principles;
• Strong problem-solving skills, ability to work independently with minimal supervision, and capacity to research and learn new technologies autonomously;
• Experience with debugging, troubleshooting, and optimizing AI/ML solutions.
 

Preferred Qualifications:

• Experience with cloud platforms (AWS, GCP, Azure) for AI/ML deployment and production implementation of AI solutions;
• Knowledge of Docker containerization, DevOps practices, MLOps, model monitoring, and CI/CD pipelines;
• Understanding of semantic search techniques, advanced embedding strategies, and experience processing unstructured data (text, images, audio) at scale;
• Proficiency with data visualization tools and techniques (Plotly, D3.js, Tableau);
• Working knowledge of web technologies fundamentals (HTML5, CSS3, JavaScript);
• Knowledge of authentication, authorization, and security best practices for AI applications.

 

Responsibilities:

• Conduct R&D in the field of artificial intelligence and machine learning;
• Prepare and develop AI concepts and prototypes to solve business challenges;
• Design and engineer effective prompts for large language models;
• Train, fine-tune, and optimize machine learning models for specific use cases;
• Develop and implement RAG (Retrieval-Augmented Generation) solutions;
• Create and integrate AI-powered bots, virtual assistants, and chatbots;
• Work with various LLM APIs (OpenAI, Anthropic Claude, Google Gemini, LLaMA, etc.);
• Implement ML models for data analysis, NLP tasks, and content generation;
• Build data processing pipelines and workflows;
• Form and test hypotheses to improve product metrics and user engagement;
• Collaborate with product teams to implement AI features that solve real user problems.

Hiring process:

• Intro call with a Recruiter — Technical Interview with the Hiring team — Offer.
 

We offer:

• Flexible work environment — you can work remotely anywhere or at our comfortable Hub in Kyiv;
• The 8-hour working day with a flexible schedule;
• Competitive salary based on your experience;
• Regular performance review and annual salary review;
• Paid sick leaves, vacation, and holidays;
• Professional development tools (reimbursement of educational courses or workshops, conferences around the world);
• Ambitious team with transparent communication and a friendly atmosphere, no micromanagement;
• Apple equipment;
• Memorable gifts for holidays.