Jobs ML / AI Engineer

We’re looking for a Senior Machine Learning Engineer to design and scale production ML systems that power real-time personalization and decision-making at scale.

In this role, you’ll own the full ML lifecycle—from transforming raw behavioral data into meaningful features, to deploying low-latency prediction APIs, to building the observability needed to keep models reliable in production.

This is a great opportunity for someone with strong applied ML and MLOps expertise who enjoys solving complex engineering challenges and building scalable, high-impact systems.

Your responsibilities will include:

• Build and productionize ML models for ranking, personalization, and customer engagement.
• Develop pipelines that transform behavioral, demographic, and contextual signals into online and offline features.
• Design and deploy low-latency APIs and decision services for real-time decision-making.
• Implement experimentation frameworks, including A/B testing and exploration-exploitation strategies.
• Operationalize the ML lifecycle: automated training, CI/CD for models, artifact and feature versioning, and online/offline parity.
• Build observability into ML systems by monitoring data quality, model drift, and decision outcomes, and triggering retraining when needed.
• Establish closed feedback loops that connect decisions to business outcomes (e.g. conversions, engagement, fatigue signals such as unsubscribes).
• Collaborate closely with product and engineering teams to balance personalization, compliance, and business value in real-world systems.

What we expect from you:

• 5+ years of experience in applied ML engineering (recommendation systems, personalization, ranking, or advertising systems).
• Strong proficiency in Python or Go, SQL, and modern ML frameworks such as TensorFlow, PyTorch, or similar.
• Strong understanding of MLOps best practices, including CI/CD for ML, containerization (Docker), orchestration (Kubernetes, Airflow, Kubeflow), model registries, and monitoring frameworks.
• Familiarity with cloud ML platforms such as Vertex AI, SageMaker, or similar, and data warehouses like BigQuery, Snowflake, or Redshift.
• Experience deploying real-time ML systems, including low-latency serving, feature stores, and event-driven architectures.
• Understanding of multi-objective optimization and trade-offs in personalization systems.
• Comfort working cross-functionally in a dynamic startup environment with the overlap within USA time zone.
• Strong spoken and written English communication skills.

Nice to have:

• Experience in martech, adtech, CRM, or large-scale personalization platforms.
• Exposure to bandit algorithms, reinforcement learning, or causal inference for adaptive decision-making.
• Experience building systems serving millions of users at scale.
• Hands-on experience with Google Cloud Platform (GCP).
• Familiarity with observability tools such as Prometheus, Grafana, Evidently, WhyLabs, or Great Expectations for monitoring data and model health.

What we offer:

• Interesting projects and technical challenges that support both professional and personal growth.
• A long-term project with stability and impact.
• A flexible, results-oriented schedule with hybrid or remote work options.
• A comfortable, modern office in Kyiv with generator and battery backup.
• Competitive salary, medical insurance, and a supportive onboarding/trial period.
• Team-building events, including parties, online activities, picnics, and more.
• The opportunity to work in a Top Employer company (DOU 2025).

The next decade of legal services will be run by AI agents. We're building the front door for the law firm of the future.
 

50+ firms run their phone and web intake on us today. Lean team, profitable, no VC. We're hiring the first AI Engineer to own the systems that make our agents actually work in production.
 

What we do
 

Lexidesk is an AI receptionist for law firms. Voice + web chat. We answer the phone 24/7, qualify the lead, book the consultation, transfer the call when it matters.

Real intake, real calls, real revenue.
 

Every law firm we onboard gets a custom AI agent, built and tuned for their practice areas, their qualification criteria, their booking rules, their transfer logic. That tuning is the product.
 

What you'll do
 

You'll own the AI side of every customer. Most of the work is prompt engineering, building, debugging, and improving the prompts that drive every conversation our agents have.
 

• Build new AI agents for every law firm we onboard, listen to how they take intake today, then design the prompts, tools, and flows that replicate it better.
• Debug live agents.
• Run test suites against every prompt change before it ships
• Listen to real call transcripts daily, find patterns across firms, propose product improvements
• Own the prompt library and the patterns that make our agents reliable at scale
• Work directly with me (Ivan, founder) on every meaningful product call
   

You'll talk to law firm owners and lawyers, learn how legal intake actually works, and turn that into prompts that ship.

Most days will be prompts and transcripts. Some days you'll write small scripts, automations, or tools to make the work faster, being able to code is a real plus, but not required.
 

Who we want

• AI-native. You use Claude, ChatGPT, or Cursor for everything. You've built your own automations. You instinctively reach for AI before reaching for documentation.
• Surgical mindset. When something breaks, you find the smallest possible fix. You hate rewrites. You like elegant, minimal changes that solve the actual problem.
• Pattern matcher. You notice the same bug across 5 different prompts and spot the underlying cause. You build mental models fast.
• Detail-obsessed. You read transcripts carefully. You catch the missing comma, the contradictory instruction, the off-by-one logic error.
• High agency. You don't wait for tasks. You see what needs to be done and do it end-to-end.
• C1+ English, you'll be on calls and reading transcripts daily.
   

Background can be anywhere, engineering, paralegal, ops, support, customer success, science PhD. Real prompt engineering work matters more than job titles. If you've shipped agents that real people use, we want to talk.
 

What we offer

• Direct line to me. No middle management, no committee.
• Real customers from day one. Every prompt you write goes live with paying firms.
• The technical core of an AI-native company at the inflection point. Profitable, growing, and you'll be the person who owns how our agents behave at scale.
• Wherever, whenever you work, we care about results, not hours.

About us

Rewire Solutions builds AI and cloud-based solutions for international clients. We are looking for motivated engineers of different levels to join our remote team.

We offer

• Remote work
• B2B contract
• Flexible schedule
• International projects
• Long-term cooperation

Requirements depend on level.

Client is looking for specialists from Junior to Senior level.

Required experience

• Experience with AI tools and LLM platforms
• Claude AI / ChatGPT / Gemini / other AI systems
• Building AI chat solutions
• AI agents and multi-agent workflows
• Prompt engineering
• AI automation
• API integrations
• Experience with modern AI ecosystems

Nice to have

• LangChain / LlamaIndex
• Vector databases
• OpenAI Assistants API
• RAG systems
• AI copilots
• Workflow automation
• Cloud AI infrastructure

Send us:

• CV
• Portfolio
• Short intro about yourself on English

Required skills:
— Experience with LLMs (OpenAI, Claude, LLaMA or similar)
— Experience building RAG systems (knowledge bases, embeddings, retrieval)
— Hands-on experience developing AI solutions in production
— Strong Python skills (FastAPI / async / API integrations)
— Experience integrating AI with databases (PostgreSQL)
— Experience with message queues (RabbitMQ)
— Understanding of real-time system architecture
— Experience with ASR (speech-to-text) and TTS (text-to-speech)
— Understanding of voice/chat AI pipeline architecture
— Experience working with APIs and microservice architecture
— Experience with high-load systems
— 3+ years of experience
— Ability to work with business logic and real client data

Nice to have:
— Experience building voice bots (inbound / outbound)
— Experience in call centers / fintech / collections
— Experience with WebRTC / streaming
— Docker / Kubernetes
— Experience in call analysis (agent scoring, script compliance monitoring)

Responsibilities:
— Develop AI chat systems working with real client data (CRM, history, statuses)
— Build RAG systems based on company knowledge bases
— Develop voice AI bots (inbound and outbound calls)
— Integrate AI with internal systems (CRM, ERP, APIs)
— Implement dialogue logic based on business scripts and protocols
— Analyze calls: transcription, quality scoring, detection of script deviations
— Automate call center operations and improve agent efficiency
— Optimize latency and stability of AI solutions in real-time environments
— Work with large volumes of data (calls, chats, customer history)
— Build and develop internal AI services for the company
— Collaborate with backend and DevOps teams to integrate AI into products

We are looking for an experienced freelance developer to join an ongoing project for an international client. The role focuses on designing and building intelligent agent systems powered by large language models, alongside contributing to broader AI and Data Science initiatives.

Important!

This role involves some travel to the Netherlands to collaborate closely with the client, run in-person consulting sessions at the WeAreBrain office in Amsterdam, and occasionally visit the client’s office. Candidates must have the flexibility and ability to travel within Europe.

About the role You will work on both client-facing projects, designing LLM-powered agents, building the data infrastructure that supports them, and helping keep AI systems reliable in production. You'll collaborate directly with cross-functional teams, so strong communication skills are essential. The engagement is project-based 

Key responsibilities

·       Python software development across client and internal projects related to AI and Data Science

·       Design and implement LLM-powered AI agents, including agent configuration and prompt engineering

·       Build and maintain data pipelines that feed and support AI systems

·       Collaborate with cross-functional teams to define requirements and deliver features

·       Stay current with emerging AI frameworks, tools, and technologies

·       Contribute to monitoring and troubleshooting AI systems in production

Required skills and experience

·       Proficiency in Python, including async patterns, API integration, and production-quality code

·       Demonstrable experience designing and shipping LLM-powered agents (please share examples or repos)

·       Hands-on experience with frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, or similar

·       Solid understanding of prompt engineering, RAG pipelines, and tool/function calling

·       Experience building and maintaining data pipelines (e.g. Airflow, Prefect, Dagster, or equivalent)

·       Familiarity with vector databases and embeddings

·       Comfortable working in cross-functional teams and translating business requirements into technical solutions

·       Fluent professional English (written and spoken) – mandatory

Nice to have

·       Experience with multi-agent systems or agentic workflows in production

·       Background in MLOps, observability, or deploying LLM systems at scale

·       Experience with cloud platforms (AWS, GCP, or Azure)

·       Exposure to evaluation frameworks for LLM applications

We are looking for an AI/ML Engineer to build and scale AI-powered solutions for real-world use cases. This is a hands-on role focused on developing agentic systems, RAG pipelines, fine-tuning workflows, and production-grade LLM integrations.

Part-time during the first month

Requirements

• 4+ years of commercial development experience (Python is a plus)
• Experience building real AI/ML applications
• Strong understanding of modern AI/ML workflows and LLM ecosystems
• Hands-on experience with ML frameworks such as TensorFlow or PyTorch (JAX is also acceptable)
• Experience with LLM APIs (OpenAI, Claude, etc.)
• Understanding of RAG pipelines and AI workflows
• Experience with APIs and third-party integrations
• Basic prompt engineering skills
• Good communication skills
• Comfortable working in a fast-paced environment

Nice to have

• Experience with LoRA, QLoRA, adapters, or other fine-tuning approaches
• Experience with LLM frameworks such as LangChain or LlamaIndex
• Experience working with clients or enterprise systems
• Background as an AI Engineer, ML Engineer, or Data Scientist

Responsibilities

• Build AI-powered features using LLMs (Claude, OpenAI, etc.)
• Develop and optimize RAG pipelines
• Create AI agents and autonomous workflows
• Fine-tune and adapt ML/LLM models for specific use cases
• Integrate AI solutions into products via APIs
• Collaborate with the team and clients to deliver production-ready solutions

Trinetix is looking for a skilled AI-Native Engineer.

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

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

Requirements 

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

Nice-to-Have 

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

Core Responsibilities 

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

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

   

What We Offer 

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