ML Tech Lead at Talentgrator

, Georgia, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Sep, 26

Salary

0.0

Posted On

05 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python 3.10+, FastAPI, PostgreSQL, LLM Architecture, RAG, AI Agents, Docker, System Design, Prompt Engineering, Async Programming, Semantic Search, pgvector, ETL Pipelines, TypeScript, Ollama, OpenAI API

Industry

Human Resources Services

Description

Our client is an established iGaming company specializing in the development of online slot games for international markets. We are looking for an ML Tech Lead to serve as the technical authority within the ML team. This is a hands-on leadership role focused on architecture, technical decision-making, and the development of AI solutions powered by LLMs, RAG, and AI agents. What You'll Do: Design and evolve LLM architectures, including RAG, multi-agent systems, tool-calling, and memory frameworks. Build and optimize semantic and hybrid search solutions using embeddings, pgvector, and reranking techniques. Develop pipelines for processing, validating, and structuring Game Design Documents (GDDs). Create prompt engineering strategies, evaluation frameworks, and AI guardrails. Integrate local and cloud-based LLMs through Ollama and OpenAI-compatible APIs. Design and maintain fault-tolerant, production-grade AI services. Contribute to the development of AI capabilities, including future automated TypeScript code generation. Lead technical discussions, architecture decisions, and code reviews. Define engineering standards, best practices, and quality benchmarks for AI development. Implement monitoring for model quality, latency, reliability, and infrastructure costs. Support and mentor engineers through technical guidance and knowledge sharing. 3+ years of commercial software development experience. Strong Python 3.10+ expertise. Hands-on experience with FastAPI, async programming, and type-safe development. Solid SQL and PostgreSQL knowledge, including schema design, indexing, window functions, and materialized views. Experience building integrations with third-party SaaS APIs, webhooks, and ETL pipelines. Practical Docker experience, including multi-stage builds and Docker Compose. Understanding of logging, monitoring, and production operations. Experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or similar. Strong system design, architecture, and problem-solving skills. Engage in a unique international web project, gaining valuable experience. 20 vacation days and 5 sick days yearly. Flexible start to the workday. Experience a dynamic work environment that avoids monotony. Opportunities for professional growth and advancement.

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Responsibilities

Serve as the technical authority for the ML team, focusing on the architecture and development of AI solutions using LLMs, RAG, and AI agents. Lead technical discussions, define engineering standards, and mentor engineers while maintaining production-grade AI services.