Senior Machine Learning Engineer
Summary
Build and scale production-ready ML infrastructure for ASR and LLM systems, collaborating with research and MLOps teams to deploy robust AI workflows.
We are a fast-growing AI startup focused on transforming industries through cutting-edge speech technologies. Our mission is to bring powerful AI solutions to production, with a strong emphasis on ASR and LLM-based systems. We’re looking for a skilled and motivated Machine Learning Engineer to join our AI Systems team. In this role, you’ll work closely with our ASR, LLM and MLOps teams to build scalable production-ready ML infrastructure and workflows.
If you’re passionate about innovation, thrive in cross-functional environments, and are eager to build advanced ML systems that make an impact, we want to hear from you.
Responsibilities:
- Design, build, and maintain robust data and ML pipelines
- Collaborate with Research Scientists to train and evaluate advanced ASR models and / or LLM workflows for production
- Design and run systematic experiments to improve the performance, efficiency, and scalability of AI workflows
- Develop and support evaluation frameworks for LLM use cases, including RAG and agentic workflows
- Benchmark models and conduct performance diagnostics across ML systems
Minimum Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field-or equivalent experience
- Proficient in Python; strong experience with UNIX-based systems and version control
- Hands-on experience with PyTorch and modern ML frameworks
- Experience training, testing, evaluating and optimizing deep learning models
- Solid understanding of data structures, algorithms and software engineering best practices
- Strong problem-solving and communication skills with an ability to collaborate across teams
Preferred Qualifications:
- Experience across the MLOps lifecycle: data ingestion, ETL, training, evaluation, deployment
- Familiarity with LLM-based systems, RAG pipelines, agentic workflows, or tools such as LangGraph
- Experience handling audio data or training ASR models
- Knowledge of tools such as Ray, Apache Iceberg, Spark, ZenML
- Experience with Docker, CI/CD workflows, Kubernetes and visualization platforms
We offer:
- Competitive compensation packages based on experience
- Hybrid remote work flexibility
- Medical insurance
- A collaborative, fast-paced, and mission-driven environment
