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Senior Machine Learning Engineer (Remote, North America)
Posted 4 days agoViewed
💎 Seniority level: Senior, 7+ years
🔍 Industry: Software Development
🏢 Company: Vivun Inc.
⏳ Experience: 7+ years
Requirements:
- 7+ years of experience building, deploying, and operating reliable data and ML systems in production environments
- BS/MS/PhD in Computer Science, Data Science, Engineering, or a related field
- Strong proficiency in writing maintainable, production-quality Python code
- Deep knowledge of AI/ML algorithms, including clustering, supervised/unsupervised learning, natural language processing (NLP), and large language models (LLMs)
- Extensive hands-on experience writing SQL and working with databases
- Experience with AI/ML observability, monitoring, and evaluation frameworks
- Advanced understanding of CI/CD pipelines (CircleCI, Harness) and API development best practices with FastAPI
- Proven experience mentoring and guiding engineering teams, with a track record of driving complex projects in dynamic environments
Responsibilities:
- You will design and develop LLM-powered AI solutions that incorporate RAG, tool calling, structured outputs, as well as knowledge and memory management.
- You will oversee the deployment and monitoring of machine learning systems in production environments.
- You will optimize and scale inference for both real-time and batch processing, ensuring low-latency and cost-efficient AI execution.
- You are an owner of quality by evaluating models/agents, both offline and online, as well as implementing and maintaining production observability tools.
- You will build and contribute to scalable data and ML infrastructure.
- You will collaborate with cross-functional teams to align AI development with business needs.
- You are adaptable and comfortable with the ambiguity of working in a highly dynamic agentic/LLM development space, evaluating emerging technologies and methodologies to continuously enhance system performance.
- You ensure adherence to security standards and data governance best practices.
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