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Lead ML/AI Engineer

Roles & Responsibilities

  • 5+ years of experience in software engineering, preferably with AI/ML or distributed systems.
  • Hands-on experience with retrieval-augmented generation (RAG) systems.
  • Deep knowledge of OpenSearch, Elasticsearch, or similar search engines.
  • Strong Python coding skills.

Requirements:

  • Design, build, and scale production-grade inference stacks for RAG-based applications.
  • Develop efficient retrieval pipelines with OpenSearch and vector databases to ensure high recall and relevance.
  • Optimize performance and latency for real-time and batch queries, and improve system reliability.
  • Mentor team members, drive architectural decisions, and lead code reviews and POCs.

Job description

For our client, we are looking for a Senior AI/ML Engineerto join an AI project and drive the design, development, and optimization of cutting-edge retrieval-augmented generation (RAG) solutions.

This role is ideal for a highly skilled engineer passionate about AI/ML systems, distributed architectures, and vector search technologies. You will play a key role in designing scalable inference stacks, optimizing retrieval pipelines, and integrating modern frameworks into production-grade applications.

Requirements



  • 5+ years of experience in software engineering, preferably with AI/ML or distributed systems.

  • Proven hands-on experience with retrieval-augmented generation (RAG) systems.

  • Deep knowledge of OpenSearch, Elasticsearch or similar search engines.

  • Strong coding skills in Python.

  • Experience with LlamaIndex, LangChain.

  • Familiarity with vector databases (Pinecone, Qdrant, FAISS).

  • Exposure to LLM fine-tuning, embeddings, semantic search, prompt engineering.

  • Background in high-scale systems handling millions of users/queries daily.

  • Knowledge of cloud infrastructure (AWS/GCP/Azure) and containerization (Docker, Kubernetes).

  • Experience with vector search, embedding pipelines, dense retrieval techniques.

  • Strong optimization skills for latency, reliability, and scalability.

  • Excellent problem-solving, analytical, and debugging skills.

  • Proactive self-starter with ownership mindset.

  • Passion for impactful technology aligned with Geniusees mission.

  • Bachelors degree in Computer Science or equivalent practical experience.

  • English: Upper-Intermediate+.

  • Candidates: Ukrainians (in Ukraine or abroad).

Responsibilities



  • Design, build, and scale production-grade inference stacks for RAG-based applications.

  • Develop efficient retrieval pipelines with OpenSearch/vector DBs ensuring high recall & relevance.

  • Optimize performance and latency for real-time and batch queries.

  • Identify and fix bottlenecks to improve system efficiency and response times.

  • Ensure observability, monitoring, and reliability of deployed systems.

  • Collaborate with teams to integrate LLMs and retrieval components into applications.

  • Evaluate and integrate modern RAG frameworks and tools.

  • Mentor team members, support architectural decisions, and uphold engineering excellence.

  • Contribute to pre-sales activities (NFR elicitation, solution architecture, risk definition).

  • Conduct discovery phases and recommend tools/libraries.

  • Lead/support code reviews, POCs, and R&D.

  • Interview external candidates and provide ad hoc troubleshooting.

What You Will Get



  • Competitive compensation & performance-based bonus - 5000 -7000 USD

  • Exciting AI startup projects with a modern stack.

  • Career development opportunities (regular reviews).

  • Professional study support, certifications, and corporate English.

  • VIP medical insurance or sports coverage.

  • Paid vacation (18 days) and sick leave.

  • Flexible working hours (start 8:00 - 11:30).

  • Unlimited remote work worldwide + cozy offices in Kyiv & Lviv with Starlink & generator.

  • Compensation for coworking (outside Kyiv & Lviv).

  • Corporate lunch, team buildings, soft skills clubs.

  • Informal and friendly work culture, no micromanagement.

  • Own charity fund.

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