Machine Learning / Data Science Engineer
Tasks
- Analyze and transform large datasets
- Attend business development events
- Collaborate with cross-functional teams
- Deconstruct business needs into data driven processes
- Deliver client presentations and proposals
- Design develop and deploy analytical solutions
- Frame data driven problems
- Implement end-to-end machine learning solutions
- Implement production scale machine learning systems
- Lead teams of junior data scientists and engineers
- Manage model lifecycle and versioning
- Optimize and scale machine learning systems
- Productionize machine learning systems
Perks/Benefits
- 1 1 care
- 401k matching
- Carrot Fertility
- Company paid stipend program
- Disability insurance
- Employee resource groups
- Employee volunteer opportunities
- Employer Sponsored Funds
- Fertility coverage
- Flexible work environment
- Group Support Sessions
- Health coverage
- Learning and development support
- Mental health support
- Mentorship
- Mentorship program
- Paid family leave
- Paid time off
- Remote work options
- Tuition support
Skills/Tech-stack
Agent Frameworks | Agent Orchestration | Agentic AI | Amazon RDS | Automation | Azure SQL | Cloud Computing | Computer Vision | Conversational UX | Databricks | DevOps | Docker | Langchain | Language Models | Language Processing | Large Language Models | Lifecycle Management | Machine Learning | Microservices | Model Lifecycle | Model Lifecycle Management | Model Management | Model versioning | Multi-Agent | Multi-agent orchestration | N8n | Natural Language | Natural Language Processing | NoSQL | Prompt engineering | Prompt evaluation | Pydantic | Python | RAG | Recommender Systems | Retrieval-Augmented Generation | Risk scoring | SQL | Scala | Snowflake | Spark | Statistical modeling | Statistics
Education
N/A
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