ML Engineer with LLM (Principal)
We are #VLteam - tech enthusiasts constantly striving for growth. The team is our foundation, that's why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. . Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of âââmeasuring outcomes, not hoursâ. Join us & see for yourself!
Project Scope
As an ML Engineer, you will dive into various projects, applying your Python, Spark, and deep learning expertise to build solutions that address strategic problems, optimize workflows, and develop common frameworks that can be leveraged across the organization. Your work will reduce complexity and enhance scalability of new projects, fostering a culture of efficiency and continuous improvement. We are looking for candidates with a strong Data Science Engineering background, focusing on ML pipelines and Gen AI, with expertise in both vendor and open-source LLM solutions.
Your key responsibilities would be
- Developing and implementing common libraries, tools, and frameworks to standardize and accelerate development processes for future projects.
- Diagnosing and resolving technical issues across multiple projects, ensuring high-quality, reusable solutions.
- Utilizing Spark and Ray to parallelize computation for machine learning tasks.
- Collaborating closely with engineering and data science teams, providing technical guidance to streamline daily work.
- Championing best practices in code quality, security, and scalability by leading by example.
- Making informed decisions to move the business forward.
Tech Stack
Python, Spark, Ray, PyTorch, TensorFlow, LLMs (OpenAI GPT, Anthropic, Llama), Google Cloud, Amazon Web Services, Kubernetes, Airflow, Docker
Project Challenges
- Implementing and deploying ML models and automated pipelines.
- Streamlining all phases of data-centric innovation, including data access, model development, productionization, testing, and monitoring of machine learning pipelines.
- Designing and reviewing machine learning code for scale and robustness.
- Collaborating with cross-functional teams to deliver ML solutions end-to-end.
- Building good engineering practices including design and architecture for reusable components across the whole organization.
Team
2 independent teams of 4-6 engineers
What we expect in general
- Hands-on experience with productionisation of Machine Learning pipelines, both as a batch process and as a service, 8+ years of experience in the area
- Hands-on experience with LLM models, preferably OpenAI and Anthropic, self-served is an advantage
- Experience with one of the popular cloud vendors
- Experience with data pipelines on Spark or Ray
- Excellent software engineering practice, including selection of the best tool for a problem
- Independence and ability to define and negotiate requirements
- Very good command of English (C1+) and clear communication skills
Donât worry if you donât meet all the requirements. What matters most is your passion and willingness to develop. Moreover, B2B does not have to be the only form of cooperation. Apply and find out!
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