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Machine Learning Engineer

Loka, IncLatAm, North Macedonia, Portugal, SerbiaPosted 30 Aug 2026

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About this role

Years from now, history will look back at this moment as a landmark for the human race, the moment generative AI began to change everything. At Loka, our ML crew is in the thick of it, shipping GenAI into production across life sciences, from cutting-edge BioLM models to agentic applications for genetic research companies. Loka is seeking a Machine Learning Engineer to join our growing team. In this position you'll build and improve machine learning solutions across multiple projects, applying your knowledge of ML and GenAI to deliver robust, scalable systems and refine them over time.

You'll grow your craft alongside an experienced ML crew on work that ships to real clients. About Loka Loka is a globally distributed tech consultancy based in Silicon Valley. In 2024, we were recognized by AWS as Innovation Partner of the Year, beating out 150,000 partners for the title. We help clients ship machine learning and GenAI into production across life sciences, as well as marketing, advertising and more. We count more than 100 certified specialists, technical experts and PhDs among our teammates, committed Lokals who bring their brilliance both to client work and to mentoring junior colleagues.

We work entirely remotely, test new ideas in our in-house incubator LokaLabs™, observe local holidays and take every other Friday off (really). What You'll Do Project Work & Logistics Take ownership of your assigned tasks and projects, accountability is key. Participate in client communications, communicating deliverables clearly. Understand business objectives and build solutions that help achieve them, along with metrics to track progress.

Collaborate cross functionally with other teams (Data Engineering, DevOps, Backend). Technical Tasks Build and maintain components of generative AI systems, including LLM powered application features and agentic workflows. Build information retrieval pipelines within established architectural patterns (data ingestion, chunking, embeddings, vector search). Contribute to evaluation frameworks and production monitoring for GenAI solutions.

Wrangle, explore and visualize data with a keen eye for data cleaning. Deploy, maintain and upgrade ML models and pipelines, analyzing model errors and designing strategies to overcome them. Write and maintain technical documentation. What You'll Bring Technical Skills Bachelor's degree in Computer Science or a related field. 2+ years of AI/ML engineering experience. Hands-on experience building GenAI solutions, prompt engineering, fine-tuning and serving LLMs, search and embeddings, using common frameworks (LangChain/LangGraph, LlamaIndex).

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Understanding of statistical, ML and deep learning algorithms. Working knowledge of cloud ML services, preferably AWS (Bedrock, AgentCore, SageMaker). Proficiency in Python and core ML libraries and frameworks (scikit-learn, PyTorch, HuggingFace, TensorFlow, Transformers). Familiarity with containerization and orchestration tools. Leadership & Soft Skills A collaborative mindset, with openness to feedback and eagerness to grow your craft.

Willingness to support and learn from more senior teammates on the ML crew. Autonomy, adaptability and a consistently positive presence on the teams you work with. Not Required but Nice to Have Building and deploying agents with common patterns (Agentic RAG, NLQ) and frameworks (smolagents, strands-agents). MLOps/LLMOps experience, preferably in AWS, along with standard tooling (MLFlow, LangFuse). Experience in consultancy environments or startups, including working directly with clients, managing projects and adapting to different settings.

Additional Requirements Excellent English, as a global team, we work entirely in English for meetings, customer calls and business communications. CV written in English. Personality Profile Curious: You strive to learn and grow into different industries with a modern tech stack. Autonomous and positive: You excel in a fully remote, globally distributed team. Team player: You enjoy a collaborative approach. Adaptable: You operate with a startup mindset and move at a startup pace.

Coachable: You take feedback well and are eager to grow your skills. Benefits Every other Friday off (26 extra days off a year) Remote-first culture Explore and Relocation programs (three months work abroad or full international relo) Paid sick days and local holidays Business English classes program Continuous Learning Support F

Source listing: greenhouse_lokainc

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