Required Qualifications: · Master’s or PhD in Computer Science, Data Science, Statistics, or related field. · 5–8 years of experience in data science and ML, with strong enterprise project delivery experience. · Proven success in building and deploying ML models and recommendation systems at scale. · 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, Lang Chain, Vector DBs, or model fine-tuning. · Advanced Python programming skills and experience with ML libraries (e.g., Scikit-learn, XGBoost, PyTorch, and Tensor Flow). · Experience with cloud-based ML/AI platforms (e.g., Vertex AI, AWS SageMaker, and Azure ML). · Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications : · Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, and CrewAI). · Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. · Working knowledge of MLOps best practices including model versioning, CI/CD for ML, and model monitoring. · Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Job Type: Full-time Work Location: In person
The DBA manager must have past job experience working with Oracle 19c and Exadata. For PostgreSQL and SQL Server, hands on experience isn't necessary but they need to be very familiar with HA, clustering, failover of all DB platforms. Cloud DB knowledge is nice to have. They are responsible for keeping the on-prem legacy environments stable and continuing any BAU work there. We are currently migrating to new Exadata machines so they will need to help lead those efforts and provide management oversight. Going into 2026, they will need to help support cloud migrations and DevOps needs which are still being figured out. Job Responsibilities: Operations (75%) · Lead response to significant database issues and help drive support teams across multiple domains (Network, Storage, Server, and Database) to find resolution. · Drive operational efficiencies (reduce unnecessary tickets/alerts, automation) · Manage on-call rotation and schedule, resource assignments, shift layout · Manage security and audit requests to provide documentation and data · Keep database standards and documentation organized and up to date · Approval of change requests, security requests. Attend weekly Change Management meetings Projects/Engineering (25%) Work intake, prioritization, task planning and estimation of DB hours Technical Knowledge: Oracle: · RAC, Exadata, GoldenGate, DataGuard PostgreSQL: · Patroni, data replication SQL Server: · Always on AG · GCP CloudSQL, AWS Aurora · DMS, Striim Leadership Skills: · Clear and timely communication with peers and leadership · Good judgement and decision making · Can handle multiple tasks and prioritize appropriately · Sees future problem areas and adjusts/prepares accordingly Stays involved in major initiatives and reacts quickly to team needs Job Type: Full-time Work Location: In person
Required Qualifications: · Master’s or PhD in Computer Science, Data Science, Statistics, or related field. · 5–8 years of experience in data science and ML, with strong enterprise project delivery experience. · Proven success in building and deploying ML models and recommendation systems at scale. · 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, Lang Chain, Vector DBs, or model fine-tuning. · Advanced Python programming skills and experience with ML libraries (e.g., Scikit-learn, XGBoost, PyTorch, and Tensor Flow). · Experience with cloud-based ML/AI platforms (e.g., Vertex AI, AWS SageMaker, and Azure ML). · Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications : · Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, and CrewAI). · Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. · Working knowledge of MLOps best practices including model versioning, CI/CD for ML, and model monitoring. · Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Job Type: Full-time Work Location: In person