ML Engineer

About Log10 Inc

Log10 is addressing the challenges around reliability and consistency of LLM-powered applications via a platform that provides AI-powered evaluations, fine-tuning and debugging tools. We are currently a team of 8 having previously worked in AI and infra roles at companies such as Intel, MosaicML, Adobe, Docker, PostEra, Starburst and Second Measure.

LLMs hold great promise but today making them reliable and improving their accuracy requires a lot of manual effort. At Log10, we are focussed on solving this challenge. We are looking for a ML Engineer to help build self-improving LLM applications. You will work directly with the founders and the AI & engineering teams to make LLMs usable in many different professional scenarios.

Responsibilities

  • Design and develop cloud-based workflows, data pipelines and compute infrastructure for production AI workloads such as LLM inference, evaluation and fine-tuning
  • Evaluate cloud computing and AISaaS providers to identify cost, accuracy, throughput and latency trade-offs. Building systems that optimize for these parameters
  • Compare closed source (OpenAI, Anthropic, Gemini) and open source LLM providers (Together, MosaicML, Replicate)
  • Develop and evaluate systems with multiple interconnected LLMs and data sources
  • Collaborate with cross-functional teams to integrate AI solutions into our product offerings
  • Stay abreast of emerging trends in AI, ML, and cloud technologies to continuously improve our systems
  • Ensure compliance with data privacy and security protocols throughout the AI lifecycle

Requirements

  • 5+ years experience designing and operating production systems
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • Experience with NLP/ML data pipelines and workflows
  • Experience with PostgreSQL, Redis and AWS services
  • Comfortable with Python, Node.js, and Go
  • Strong grasp of distributed computing fundamentals
  • Self-directed and enthusiastic about solving complex problems

Nice to have

  • Familiarity with prompt programming and large language models
  • Experience in developing and deploying large-scale AI systems
  • Experience with ML model lifecycle management tools
  • Knowledge of advanced ML techniques, including deep learning and reinforcement learning
  • Contributions to open-source projects or published research in relevant fields

We provide a competitive salary, equity, health/dental/vision insurance and the chance to develop foundational systems that will redefine how companies build AI. This is a high-impact, high-autonomy role for someone eager to take on technical ownership and leadership. If this matches your background and ambitions, we'd love to hear from you!



Engineering

San Francisco, CA

Remote (United States)

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