The partner company is looking to build scalable, high-performance AI-driven applications and needs a Senior Machine Learning Engineer specializing in Generative AI to design, develop, and maintain the necessary machine learning infrastructure and models.
Requirements
- 5+ years of backend engineering experience in languages such as Python, Go, or Java.
- Experience building and deploying ML-driven multi-tenant applications in production environments.
- Familiarity with ML technologies and workflow tools such as Jupyter, Dagster, MLFlow, KubeFlow, Triton Server, LLMs, DVC, and Postgres.
- Hands-on experience with modern ML techniques, including LLMs, RAG, prompt engineering, fine-tuning, and multi-modal models.
- Proficient in distributed systems, designing scalable and redundant services for large datasets.
- Experience working with public cloud platforms (AWS, GCP) and container orchestration (Kubernetes, GKE).
- Experience with GitOps, IaC, configuration-driven systems, and automation workflows.
Responsibilities
- Design, implement, and maintain machine learning models, infrastructure, and tooling for AI-powered product features.
- Build scalable, resilient backend services to support data integration, event processing, and distributed workflows.
- Develop internal platforms and APIs to make AI capabilities accessible across product teams.
- Operate in cloud environments and distributed systems, ensuring performance, scalability, and observability.
- Collaborate with product and development teams to explain data lifecycles, machine learning tradeoffs, and best practices.
- Consult across teams on machine learning patterns, anti-patterns, and design choices to ensure excellent end-to-end user experiences.
- Work with stakeholders to translate product goals into actionable ML engineering plans.
Other
- Mentor engineers, promote best practices, and contribute to a culture of high-quality, testable, and maintainable code.
- Strong problem-solving, collaboration, and communication skills, with a bias for action.
- Proven track record of delivering complex projects on time in enterprise-grade production environments.
- Fully remote flexibility across the United States.
- Background in data science, predictive analytics, or real-time audio and NLP pipelines.
