Jobs ML / AI

We are looking for an AI Application Engineer to build AI-enabled applications, internal tools, and agentic workflows using modern AI coding and development platforms such as Codex, Claude Code, ChatGPT, Claude, Vercel, and related APIs/SDKs. This person will be responsible for turning business needs into working software quickly. They will use AI-native development tools to accelerate prototyping and production delivery, while still applying strong software engineering judgment around architecture, security, testing, maintainability, and user experience. This is not a research role and not a pure prompt-engineering role. It is a hands-on builder role for someone who can design, build, test, deploy, and iterate on AI-powered applications and agents.

The position requires 3-4 hours of overlap with the Pacific time zone.

Key Responsibilities:

• Build AI-powered web applications, internal tools, prototypes, and workflow automations using modern full-stack technologies.
• Develop and configure agents in platforms such as ChatGPT, Claude, and related enterprise AI environments.
• Use AI coding tools such as Codex, Claude Code, Cursor, GitHub Copilot, or similar tools to accelerate software development while maintaining quality standards.
• Build applications using frameworks and platforms such as Next.js, React, TypeScript, Node.js, Python, Vercel, APIs, databases, and cloud services.
• Integrate large language models into applications using APIs, SDKs, tool calling, function calling, retrieval, memory, structured outputs, and workflow orchestration.
• Translate business requirements into working software, including lightweight product discovery, technical design, prototyping, testing, deployment, and iteration.
• Evaluate where an AI agent, chatbot, workflow automation, or traditional application is the right solution.
• Create reusable templates, components, agent patterns, and development practices that help teams build faster.
• Partner with business stakeholders, product managers, designers, engineers, data teams, security, and legal/compliance partners as needed.
• Ensure applications and agents are secure, reliable, explainable enough for the use case, and aligned with company standards.
• Measure adoption, usability, quality, and business impact of AI-enabled solutions.

Required Qualifications:

• 7+ years of software engineering experience, preferably in full-stack, product engineering, internal tools, platform engineering, or automation roles.
• Strong proficiency in TypeScript/JavaScript, especially React, Next.js, Node.js, APIs, and modern frontend/backend development.
• Working knowledge of Python for scripting, automation, API integrations, data handling, or agent workflows.
• Experience building and deploying web applications using platforms such as Vercel, AWS, GCP, Azure, or similar cloud/deployment environments.
• Hands-on experience with generative AI tools such as ChatGPT, Claude, Codex, Claude Code, Cursor, GitHub Copilot, or similar AI development tools.
• Experience integrating LLMs into applications using APIs, SDKs, prompt patterns, structured outputs, retrieval, tool calling, or workflow automation.
• Strong software engineering fundamentals: clean code, testing, Git, code review, debugging, logging, documentation, security awareness, and maintainability.
• Ability to work directly with non-technical stakeholders and turn ambiguous business problems into working solutions.
• Strong judgment about when to use AI, when not to use AI, and how to keep a human in the loop for higher-risk workflows.

Preferred Qualifications:

• Experience building AI agents, custom GPTs, Claude projects, workflow agents, copilots, or enterprise AI assistants.
• Experience with Vercel AI SDK, LangChain, LlamaIndex, Semantic Kernel, OpenAI APIs, Anthropic APIs, or similar frameworks.
• Experience with retrieval-augmented generation, vector databases, embeddings, search, knowledge bases, and enterprise data integrations.
• Experience building internal productivity tools, employee-facing workflows, operations tools, or business process automation.
• Experience with authentication, permissions, secure data handling, audit logging, and enterprise deployment patterns.
• Experience designing lightweight user experiences for AI tools, including chat interfaces, agent dashboards, task flows, and approval workflows.
• Comfortable working in fast-moving, prototype-to-production environments.

s a Foundry AI Developer, you will be at the forefront of building the “Enterprise Brain” by architecting intelligent systems that bridge the gap between massive data lakes and actionable AI. Your primary objective is to design, develop, and optimize an agentic ecosystem using Microsoft Fabric, Azure AI Search, and the Model Context Protocol (MCP). You will be responsible for creating the “nervous system” that allows LLMs to interact securely with proprietary data and internal tools while maintaining peak performance and cost efficiency.

Key Responsibilities

1. Unified Knowledge Engineering (Fabric & AI Search)
The Focus: Building the "Enterprise Brain" by linking Microsoft Fabric’s OneLake to Azure AI Search / Foundry IQ.
Key Responsibilities:
Developing Fabric Data Agents that serve as live conduits between structured lakehouse data and the Foundry Hub.
Configuring Azure AI Search as a vector-enabled index to ingest unstructured data from Fabric, enabling "Agentic RAG" where the agent decides when to pull deep historical data vs. real-time telemetry.
Implementing Foundry IQ skills to handle semantic chunking and multimodal embeddings, ensuring the LLM receives highly relevant context.
2. Python-Based MCP Server Architecture
The Focus: Creating a secure "Nervous System" that allows LLMs to act on proprietary systems using the Model Context Protocol (MCP).
Key Responsibilities:
Developing custom MCP Servers in Python (using asyncio and FastAPI) to expose private APIs and local tools as "Functions" that the agent can invoke.
Hub Registration: Registering these servers within the Foundry Hub as persistent connections, allowing multiple AI agents to share the same toolsets securely.
Managing identity and access through Foundry Control Plane, ensuring that agent "tool-use" follows enterprise security policies (OAuth/Managed Identities).
3. Model Orchestration & Token Optimization
The Focus: Selecting the "Right Model for the Right Task" to maximize performance while minimizing token burn.
Key Responsibilities:
LLM Evaluation: Using Foundry’s Evaluation Dashboard to run "LLM-as-a-judge" benchmarks, comparing models (e.g., GPT-4o for complex reasoning vs. Phi-3 or Llama 3 for extraction) to find the most cost-effective fit for specific sub-tasks.
Token Efficiency: Designing Python-based "Routing Logic" that sends simple queries to small language models (SLMs) and reserves expensive LLMs for complex orchestration.
Observability: Monitoring "Token Burn" per agent run in the Foundry portal to identify prompt bloat and optimize system instructions for brevity without losing accuracy.

About the company: United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide
 

About your role: We’re looking for an AI Engineer who wants to build production-grade AI systems, not just experiment with demos. This is a high-ownership, greenfield role where you’ll help build our AI platform from scratch, working directly with the Head of AI.  You’ll own initiatives end-to-end — from discovery and architecture decisions to production delivery — and play a key role in shaping how AI is used across the company.

You’ll work with a modern AI stack including Claude/OpenAI/Bedrock, RAG pipelines, eval frameworks (Promptfoo, Ragas, LangSmith), and agentic patterns. This role is ideal for someone who enjoys autonomy, strong engineering ownership, and proactively identifying the next highest-leverage opportunity to drive into production.

In this role, you will:

• Design and build RAG and automation workflows inside our VPC environment.
• Create integrations across engineering, communication, and knowledge-management systems (Jira, Confluence, Slack, Google Drive, Git).
• Develop AI-powered pipelines for code quality checks, ticket auto-classification, documentation updates, release notes, and meeting summaries.
• Work on prompt engineering, model selection and routing (Haiku / Sonnet / Opus), and workflow optimization.
• Build evaluation and regression frameworks for AI workflows to prevent model-upgrade regressions.
• Create lightweight dashboards for engineering leads to surface delivery patterns and bottlenecks.
• Own initiatives end-to-end: scope → design → ship → measure → iterate.

It’s all about you:

• 5+ years of production experience with Python (services, async, API integrations, clean and testable code).
• Hands-on experience with LLM APIs in production: Anthropic Claude (Opus/Sonnet/Haiku), OpenAI, AWS Bedrock.
• Strong understanding of RAG systems: chunking, embeddings, hybrid search, re-ranking, grounding/citations.
• Prompt engineering + structured outputs + tool/function calling.
• Experience with eval/regression frameworks: Promptfoo, Ragas, LangSmith, or custom evaluation harnesses.
• Agentic patterns: ReAct, function-calling loops, fallbacks.
• Vector databases: pgvector, Pinecone.
• Workflow orchestration: n8n, Airflow, or custom orchestration systems.
• Observability: token-spend tracing, latency monitoring, model routing.
• Solid AWS fundamentals: IAM, Lambda, S3, CloudTrail — comfortable deploying inside VPC environments independently.
• CI/CD + pipeline hooks (GitLab/GitHub), webhooks, event-driven architectures.
• Basic SQL skills for analytical queries and metrics dashboards.
• Driver mindset: proactively identifies the highest-leverage opportunity and drives it to production
• B2 English level

Would be a plus:

• Real REST integrations with 2–3+ APIs
• Experience with workflow orchestration tools.
• Prompt evaluation tooling such as  LangSmith is nice to have
• Experience with Docker
• RAG experience: embeddings and vector stores (pgvector, Pinecone, or similar) for knowledge base use cases

What we offer

Care and support: 

• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule 
• Modern equipment or depreciation of your own tools
   

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   

Hiring process:

• Intro call
• Technical Interview
• Final Interview
• Reference check
• Offer

We are seeking an experienced AI Edge Device Developer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and optimizing AI algorithms and models for deployment on edge devices. Excellent problem-solving skills, attention to detail, and the ability to work in a fast-paced environment are essential for success in this role. If you are passionate about pushing the boundaries of AI at the edge and thrive in a collaborative environment, we encourage you to apply.
 

About:

Our client is developing electro-mechanical devices for dairy farms, pulsators and automatic detachers. The solution is leading in the industry with advanced cow monitoring solutions based on activity and rumination sensors.

Responsibilities:

• Designing, developing, and optimizing computer vision pipelines for deployment on edge devices;
• Cross-compiling solutions for various CPU/NPU/VPU types. Perform performance analysis and optimization to ensure real-time processing capabilities on edge devices;

• You will face real-life challenges and complexities emerging from working closely with our AI researchers to provide market leading products.

   

Requirements:

• 5+ years experience in Python, C/C++;
• Hands-on experience with GStreamer or DeepStream;
• Experience with TensorRT, ONNX;
• Experience with processing multiple video streams;
• Hand-on experience with ML accelerators, such as: Nvidia Jetson, Google Coral;
• Proficient in Linux;
• Proficient in Git version control;
• Bachelor's Degree in Computer Engineering, Computer Science or related fields;

• At least Upper-Intermediate English level.

   

Would be a plus:

• Understanding of concepts in signal processing, machine learning and computer vision;
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch;
• Neural network models quantization and pruning;
• Familiarity with building Docker images (Docker files);
• Understanding of CI/CD processes for production code, unit tests, and regression testing;

• Knowledge of CUDA.

   

We offer:

Professional Development: Free English courses, free access to the corporate Udemy account, corporate digital library subscription, possibility to participate and share your knowledge as a speaker in our internal meetups.

Benefits: 100% paid vacation and sick leaves, opportunity to accumulate part of the own salary in the company in dollar terms.

Overview
We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This is a hands-on role focused on applied machine learning and data engineering, ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;
• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences;

• Stay up to date with recent ML/AI advancements and evaluate promising methods for future implementation.

   

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

Reply.io is a fast-growing SaaS company helping businesses automate and scale their sales outreach.

We're looking for a Prompt Engineer to work with large language models (GPT, Claude, and others) — enhancing their performance through prompt tuning and conducting research using AI coding agents.

This is hands-on, focused prompt work — sometimes repetitive, always precise — with direct impact on how Jason AI and our other AI-powered features perform.

If your success formula is: 👉 Right model + Right prompt structure + Right evaluation + Continuous iteration — you'll thrive here.

🎯 What you'll do:

• Refine existing prompts — continuously improve quality across our AI features, from simple categorisation to complex, highly personalised email sequence generation, including addressing minor bugs in the results
• Develop new prompts for upcoming AI tools and workflows aimed at making customers' work easier and more efficient
• Use AI coding agents to research, prototype, and validate prompt approaches
• Test prompts on newly released models (Claude, GPT, and others) — compare performance, document trade-offs, recommend upgrades
• Partner with sales, growth, and dev teams to make sure AI outputs match real business needs
• Embrace the detail-oriented, sometimes repetitive nature of prompt tuning — consistent quality matters more than novelty here
• Stay ahead of LLM advancements — new models, new techniques, new evaluation methods

🧩 Requirements:

• 0.5–1 year of experience as a Prompt Engineer, understanding of AI agent workflows, or light scripting/development background (will be a plus — candidates without prior experience are also welcome to apply)
• Passion for AI and hands-on experience with LLMs (GPT, Claude, or similar)
• Prompt tuning expertise — you've optimised prompts and can articulate what worked, what didn't, and why
• Attention to detail and patience for focused, methodical iteration — the role involves repetitive refinement with consistent quality
• Strong communication — you can translate between business needs and LLM behaviour, working across sales, growth, and dev teams
• English proficiency (B2+) — written and spoken
• Willingness to learn — you actively follow AI trends and test on new models as they release

🎁 What we offer:

• Ownership of prompts that ship into customer-facing AI features used by sales teams every day
• Work with cutting-edge LLMs — Claude, GPT, and whatever ships next; premium API access covered
• High autonomy — no micromanagement, no bureaucracy, real ownership
• 100% remote with minimal meetings
• Coverage of professional courses, gym memberships, or therapy sessions
• AI-first culture — we actively use and cover costs of premium tools
• 15 paid vacation days, 🇺🇦 national holidays & ~10 days of Christmas vacation
• Sick leaves without limitations
• Access to internal training, literature, and knowledge sessions

If you love prompting, think in iterations, and are excited to shape how Jason AI performs — we'd love to hear from you!

Atlas Technica’s mission is to shoulder IT management, user support, and cybersecurity for our clients, who are hedge funds and other investment firms. Founded in 2016, we have grown 100% year over year through our uncompromising focus on service.

We value ownership, execution, growth, intelligence, and camaraderie. We are looking for people who share our Core Values, thrive, and contribute to this environment while putting the customer first. At Atlas Technica, we offer a competitive salary, comprehensive benefits, and great perks to our global Team. We strive to maintain a professional yet friendly environment while promoting professional and career development for our Team Members. Join Atlas Technica now!

Design and deploy intelligent chatbots using Foundry Workflows, Microsoft Agent Framework, OpenAI. Build and operate multi-agent orchestration pipelines with Azure AI Foundry and Model Context Protocol (MCP). Integrate AI with enterprise systems via RESTful APIs, ensuring compliance with security and privacy standards. Stay current with LLM advancements, collaborate across teams, and mentor junior engineers.

Responsibilities:

AI Agent & Chatbot Development

• Design, build, and deploy intelligent conversational agents using Foundry Workflows, Microsoft Agent Framework, OpenAI.
• Develop prompt strategies and manage datasets to support context-aware, multi-turn dialogue and accurate responses.
• Conduct rapid prototyping to validate technical feasibility and demonstrate business value of AI-driven solutions.
• Design agentic loops with task decomposition, state passing between agents, and workflow enforcement for multi-step ticket resolution.

• Implement structured error responses and graceful degradation in agent tool calls, including timeout handling, retry logic, and fallback cascades.

   

Data & Model Engineering

• Build and maintain data ingestion and indexing pipelines for Azure AI Search and Cosmos DB.

• Evaluate and optimize AI system performance for accuracy, scalability, latency, and cost-efficiency.

   

System Integration & Architecture

• Architect and implement integration between AI and enterprise systems (e.g., ConnectWise PSA, Confluence, etc.) using RESTful APIs.
• Implement and maintain MCP servers (Model Context Protocol) for secure, typed tool integration between AI agents and enterprise APIs.
• Deploy containerized services to Azure using multi-stage builds and Azure Pipelines CI/CD.
• Security, Compliance & Governance
• Ensure AI systems comply with data privacy regulations (e.g., GDPR) and enterprise-grade security standards.

• Implement access controls, data encryption, and audit logging for sensitive AI workflows.

   

Research & Innovation

• Stay current with evolving LLM technologies, frameworks and methodologies.

• Evaluate emerging tools and techniques to continuously improve solution quality and delivery speed.

   

Collaboration & Leadership

• Work closely with cross-functional teams to interpret business requirements and recommend LLM-driven solutions.
• Contribute to technical and architectural decisions, ensuring alignment with strategic goals.

• Mentor junior engineers and support knowledge sharing across the team.

   

Operational Excellence

• Take ownership of incident resolution, and bug fixes.
• Create and maintain technical documentation for AI systems, models, and integration workflows.

Requirements:

• English level — B2 or higher
• 5+ years of experience in AI engineering and .NET software development (.NET 10, ASP.NET Core/WebAPI, C#) with frontend experience in React 19 / Next.js 15 / TypeScript, with a focus on Azure-based solutions.
• Experience building intelligent chatbots and autonomous agents (Agentic AI) that perform real actions, plan, reason, and act with minimal human input; familiar with multi-agent orchestration and agent memory.
• Strong expertise in embeddings, search, and prompt engineering.
• Strong understanding of large language models (LLMs), their limitations, and modern capabilities (e.g., GPT, Claude, Gemini).
• Hands-on experience with Azure AI services (Azure AI Foundry, Azure OpenAI, Azure AI Search) and hands-on experience with MCP or similar protocols for secure, scalable integration between AI agents and enterprise systems.
• Familiarity with multi-agent orchestration patterns: coordinator-subagent workflows, maker-checker validation, signal-based confidence scoring, and context preservation across multi-turn interactions.
• Experience designing prompts with explicit evaluation criteria, few-shot techniques, structured output via JSON schemas, and validation/retry loops for reliable LLM responses.
• Awareness of AI-specific security concerns: PII handling, data boundary enforcement, prompt injection prevention, and compliance considerations (e.g., GDPR).

• Ability to write clean, maintainable, and testable code following SOLID principles and Clean Architecture patterns.

   

Desirable Qualities:

• Understanding of AI solution architecture patterns: LLM gateway/service layer, retrieval layer, orchestration/agent layer, and evaluation/observability layer.
• Experience testing AI-enabled components using deterministic seams (mocked LLM clients, retrievers, tools), scenario-based tests, and regression/evaluation datasets for non-deterministic outputs.
• Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
• Familiarity with AI/ML versioning practices: prompt version control with semantic tagging, evaluation baseline tracking, dataset versioning, experiment reproducibility.
• Familiarity with deploying, monitoring, and maintaining ML models in production environments.
• Experience with Azure Cosmos DB, Azure Container Apps, Docker containerization
• Familiarity with CI/CD pipelines and DevOps practices.
• AI-102
• Experience with Application Insights telemetry, distributed tracing.
• Prior experience integrating AI agents with enterprise platforms like ConnectWise PSA, Confluence, SPO, etc.

Atlas Technica is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Pozotron is seeking an AI Engineer to join our development team. Our growing development team, based in Ukraine, is dedicated to creating incredible technology for audio production. The AI Engineer will be an instrumental part of our team, focusing on improving functionality, flexibility and performance of our AI tools.

Required:

• 3+ years of experience with Python
• 2+ years of experience with Machine Learning
• 2+ years of experience with Data Analysis
• Experience with NN inference (ONNX, vllm, etc.)
• Experience with multiple facets of LLMs, including fine-tuning, inference, and orchestration
• Experience with agentic AI, including vibe coding. Experience with multiple models preferred.
• Knowledge of Statistics
• Intermediate+ level of English
• Excellent problem-solving skills and attention to details
• Good communication skills

Nice to have:

• Bachelors or Masters degree in Computer Science, Information Technology, Mathematics, Physics or Engineering
• Knowledge of RDBMS
• Experience with Audio and Text processing
• Experience with Django
• Experience with Cython
• Experience with GCP
• Experience with Docker and Kubernetes
• Experience with Linux

We offer:

• Fully remote work
• Competitive compensation, benefits, and bonus plans
• Health insurance

We seek a Strong Middle ML / AI Engineer to join our team on a humanitarian transparency platform. This is a hands-on engineering role focused on building machine learning models and data pipelines — primarily around deduplication, anomaly detection, and statistical analysis of humanitarian data.

 

🧙‍♂️ In This Role You Will

• Design, build, and maintain ML models for deduplication, anomaly detection, and predictive analytics.
• Work with structured humanitarian data — beneficiary records, financial transactions, procurement flows.
• Build and maintain data processing pipelines using Python (Pandas, NumPy, scikit-learn).
• Collaborate with the backend team to expose ML/AI outputs via APIs.
• Monitor model performance and iterate based on real-world feedback.
• Document your work and support knowledge sharing within the team.
  
  
   

🎯 You May Be Interested If

• You enjoy working with messy, real-world data and turning it into reliable ML outputs.
• You care about model quality, reproducibility, and practical impact.
• You're comfortable applying classical ML approaches to solve concrete business problems.
• You're excited to collaborate in a remote, cross-functional environment.
• You value autonomy, clear communication, and working in a supportive, small-team setting.
  
   

👌 Role Requirements

• 3+ years of experience in ML engineering, data science, or a closely related role.
• Strong Python skills: Pandas, NumPy, scikit-learn.
• Experience building and deploying ML models in production environments.
• Solid understanding of data pipeline design and data quality practices.
• Familiarity with cloud platforms (Azure or AWS) for ML workloads.
• Proficiency with Git and standard development tooling.
• English proficiency at B1 level or higher.
   

Nice to have:

• Experience with PyTorch or TensorFlow.
• Hands-on experience with LLM integrations (OpenAI, Anthropic, or similar).
• Familiarity with ML experiment tracking tools (e.g. MLflow, Weights & Biases).
• Experience with GIS or geospatial data.
• Background in fraud detection, entity resolution, or deduplication tasks.
• Familiarity with Docker and CI/CD workflows for ML pipelines.
  
   

💻 Working Conditions

• Employment Type: Full-Time
• This is a fully remote position with the entire team across Ukraine.
• 20 working days of paid vacation per year.
• The team collaboratively defines deadlines, ensuring a balanced and manageable workload. The focus is on delivering commitments on time.
• Flexible working hours to promote a healthy work-life balance.

COMPANY
Arcyn is creating an AI-powered compliance checker for architectural design — an Autodesk Revit plugin that automatically checks designs against regulations. Architects get instant feedback on violations as they design in Revit, instead of waiting weeks for permit reviewers to tell them what’s wrong.

We’ve just closed the seed round and are building the core technical team. We’re now a team of 4 with a track record of building complex technical products. This is a chance to join at the ground floor, shape product architecture and solve genuinely hard AI problems.

KEY RESPONSIBILITIES

• Design and maintain modular, multi-step ML and LLM workflows for compliance automation, combining classical ML techniques with LLM-based components where appropriate
• Lead the data science and ML work end-to-end: problem framing, data exploration, experimentation, evaluation, and productionization
• Integrate multiple LLM providers (e.g., OpenAI, Anthropic, Perplexity) into a cohesive orchestration pipeline.
• Build cost-optimized batch processing and intelligent API request strategies.
• Translate complex regulations into structured, machine-executable logic.
• Develop and validate automatically generated code to ensure correctness, safety, and performance.
• Collaborate with domain experts to refine logic interpretation and edge case handling.
• Maintain high-quality, well-structured Python codebases with clear separation of concerns.

REQUIREMENTS
Must-have:

• 8+ years of professional experience in data science, ML engineering, or closely related roles
• Strong foundation in ML/DS fundamentals: feature engineering, model selection, evaluation methodology, error analysis, and handling messy real-world data
• Strong Python skills, including experience writing production-grade, modular code.
• Proven track record building multi-step LLM workflows (LangChain, LangGraph, or similar).
• Experience in structured code generation and validation.
• Strong debugging skills and comfort working with complex, evolving systems.

Nice-to-have:

• Experience with compliance automation, technical regulations, or domain-specific rule translation.
• Familiarity with Pydantic models or other type-safe data management frameworks.
• Background in developer tooling or systems requiring high reliability and reproducibility.
• Experience optimizing LLM API usage for both cost and speed.

WHAT WE OFFER

• Full-time remote role aligned with CEST
• B2B set-up via SP account
• Flexible work arrangements and competitive compensation
• Freedom to architect solutions using the best tools for the job
• Collaboration with a multidisciplinary, innovation-driven team
• Opportunity to shape a new AI product from the ground up at an early stage

Responsibilities:

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

Must have:

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

Nice to have:

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

• Надаємо бронювання від мобілізації

AI Agent Engineer 

About the Role

We are looking for a skilled AI Agent Engineer to build advanced AI agents and autonomous workflows powered by modern LLM technologies.

You will work on production-grade agentic systems, orchestration frameworks, memory systems, tool calling, and multi-agent architectures.

This role is ideal for engineers passionate about the future of autonomous AI systems.

Responsibilities

• Develop AI agents and agentic workflows
• Build and optimize multi-agent systems
• Implement RAG pipelines and memory architectures
• Integrate external tools and APIs into AI systems
• Work with orchestration frameworks such as LangGraph, CrewAI, or AutoGen
• Improve reliability, evaluation, and observability of AI systems
• Deploy and maintain production AI applications
• Collaborate with product and engineering teams

Requirements

• 3+ years of software engineering experience
• Hands-on experience with LLM applications and AI agents
• Experience building AI agents or agentic workflows
• Strong Python skills
• Experience with:
  • LangGraph / CrewAI / AutoGen
  • OpenAI APIs
  • RAG systems
  • Vector databases
  • Prompt engineering
  • Tool calling
• Experience deploying production systems
• Understanding of agent memory and orchestration concepts

Nice to Have

• MCP experience
• AI evaluation frameworks
• AI observability tools
• Fine-tuning experience
• Open-source AI contributions
• Personal AI projects / GitHub portfolio

We Offer

• Remote-first environment
• High-impact AI projects
• Modern AI stack and technologies
• International team
• Long-term collaboration

We're hiring a Senior Software Engineer to join us for a long-term engagement with a fast-growing UK travel tech client. The role focuses on owning and evolving their production document AI pipeline (OCR plus ML inference on passport and ID documents, CPU only deployment, no GPU).

This is hands-on production engineering, not research. You'll be improving OCR accuracy, optimizing CPU inference (INT8 quantization, ONNX Runtime, batching), refactoring pipeline complexity, and improving observability of a system serving enterprise clients at scale.

What you'll do:

• Take ownership of the existing OCR and document understanding pipeline in Python
• Optimize ML inference for CPU production (ONNX Runtime, quantization, batching, kernel tuning)
• Improve OCR accuracy, latency, throughput, and memory efficiency
• Refactor architectural complexity and reduce technical debt
• Work across ML systems, backend services, APIs, and data pipelines
• Help shape architectural decisions as the platform scales

Required:

• 5 plus years of professional Python software engineering
• Strong experience with OCR and document processing pipelines
• Familiarity with LayoutLMv3, Doctr, PaddleOCR, EasyOCR, Donut, or DocFormer
• Production ML systems experience (not just notebook experimentation)
• ONNX Runtime, quantization, TorchScript, or related CPU inference optimization
• Strong understanding of PDFs, image preprocessing, bounding boxes, and page segmentation
• Experience with systems serving external customers at scale

Nice to have:

• HuggingFace Transformers production experience
• Enterprise SaaS or aviation/travel tech background
• MLflow, Vertex AI, or similar ML operations tooling
• Distributed systems and backend API design experience

Engagement:

• Fully remote
• Long-term (6 plus months) with potential to expand engineering ownership over time
• Part-time (25-30 hrs/week) or full-time (35-40 hrs/week), depending on candidate availability
• Flexible timezone (engagement requires some overlap with UK working hours)

How to apply:
Send a short note covering relevant OCR / document AI work, production ML systems you've shipped, CPU inference optimization experience, GitHub or LinkedIn, current availability, and timezone.

Who We Are

At Bennett Data Science, we've been pioneering the use of AI, predictive analytics, and data science for over a decade for some of the biggest brands and retailers. We're at the top of our field because we focus on delivering actionable AI for our clients. Our deep experience and product-first attitude set us apart from other groups and gets us the business results our long-term clients want.

Why You Should Work With Us

You'll be exposed to a wide range of clients who are at the cutting edge of innovation in their field and get to work on fascinating problems, supporting real products, with real data. We help lots of companies, from some of the largest companies in the world to small startups in Silicon Valley who are building the next big thing.

About

We are hiring for a remote applied AI consulting firm that builds production AI systems for clients. The company works on real business workflows, private data, and deployed software. The team is small, senior, and focused on systems that survive production use. The company values clear ownership, strong engineering judgment, and direct communication.

The role

You will own a reusable agent platform that powers every agentic client engagement. The platform will cover orchestration, tool calling, retrieval, evaluation, deployment, monitoring, and common data connectors. You will take the current foundation forward and make it stable, documented, and easy for other engineers to use. You will make key architecture choices and keep the system simple enough to extend across different client environments. You will work closely with senior engineers who adapt the platform to client workflows.

You will:

• deliver a scalable agentic platform from early prototypes to a deployable, sellable product
• build the core services that let agents plan work, use tools, retrieve data, and complete tasks safely
• apply proven practices for reliability, security, monitoring, cost control, and recovery
• create clear ways to test quality, review production behavior, and improve the platform based on real usage
• make the platform easy to deploy, operate, and adopt across client environments
• write clear guidance for engineers who build on the platform.

Required:

• LangGraph in production is essential. You have designed, shipped, and maintained LangGraph graphs in production: state management, checkpointing, multi-agent orchestration, and human-in-the-loop interrupts
• 7+ years shipping production software, with at least 2 years on LLM-powered systems running in production (not an internal tool)
• Strong Python. Comfortable with FastAPI or equivalent for serving, Postgres or equivalent for state, and Docker for deployment
• Built or maintained a non-trivial agent system end to end: orchestration, tool calling, retrieval, evaluation, deployment
• RAG experience: hybrid retrieval, chunking strategy, evaluation, citation grounding, no-answer fallback
• Production cloud deployment on AWS, GCP, or Azure. Comfortable with continuous integration and deployment, observability, on-call
• Evaluation discipline: you measure on production traffic, you write the eval harness, you do not ship without it
• Written and spoken English at B2 or above
• Can take an ambiguous problem and ship a working system without daily supervision

Strong plus:

• Open-source contributions to LangGraph or LangChain, or you have published LangGraph patterns others use
• You have built a platform or framework that other engineers use. You have written the documentation for it
• Comfort with a second orchestration approach beyond LangGraph (Claude Agent SDK, AutoGen, CrewAI, or hand-rolled) so you can make the right call per client
• Fine-tuning experience: LoRA, PEFT, instruction tuning, distillation
• Open-source contributions to LlamaIndex, DSPy, Haystack, or similar
• Background in classical ML (scikit-learn, gradient boosting, time series)
• MCP (Model Context Protocol) experience or interest
• Shopify ecosystem, Snowflake, or Postgres extensions experience
• Ukrainian native or fluent

You get full ownership of a core production system with senior peers and direct access to decision makers.
 

You you also get remote work with flexible daily hours and authority to shape engineering standards for agent systems.

We’re on the hunt for a talented AI/ML Engineer to design, implement, and optimize cutting-edge AI/ML solutions. If you thrive on solving complex problems and creating production-ready models, we’d love to hear from you!

.  What You’ll Do:

• Develop and fine-tune AI/ML models for performance and scalability.
• Enhance production models, debug issues, and ensure reliability.
• Work with cross-functional teams to shape future AI/ML innovations.
• Explore emerging AI/ML technologies and recommend tools/frameworks.
• Build robust pipelines using Python, SQL, Docker, and more.

.  What We’re Looking For:

• Strong experience in AI/ML, data science, or data engineering.
• Expertise in Python, TensorFlow, Keras, Scikit-learn, and Generative AI.
• Familiarity with Docker, Streamlit, and data tools like Pandas and SQL.
• Strong communication skills and the ability to work independently.

• English: Upper-intermediate or higher.

   

  What We Offer:

✔️ 18 vacation days + 12 sick leaves annually.
✔️ A high-tech workplace (MacBook Pro + Dell monitor).
✔️ Exciting projects with cutting-edge technologies.
✔️ Flexible work hours and competitive salary.
 

Ready to shape the future of AI/ML with us? 🚀 Apply now and be part of something extraordinary!