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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Engineer

NovaMind AI Labs
San Francisco
Salary Estimate
USD 150.000 – USD 210.000
Posting Time
7 Mei 2026
Deadline
7 Mei 2027

Job description

NovaMind AI Labs is seeking a seasoned Senior AI Engineer to join our San Francisco team. You will design and deploy cutting-edge AI/ML solutions that power product experiences across industries. This is a hands-on, leadership-focused role with opportunities to influence architecture, data strategy, and model governance.

What you'll do as part of the team: contribute to architecture decisions, collaborate cross-functionally, and push the boundaries of applied AI. We offer a competitive compensation package, equity, and comprehensive benefits.

Responsibility

  • Lead the design, development, and deployment of scalable AI/ML models, including large language models and multimodal systems.
  • Collaborate with data scientists, data engineers, and product teams to define data features and success criteria.
  • Build end-to-end ML pipelines from data ingestion and preprocessing to model training, evaluation, and deployment (MLOps).
  • Implement monitoring, alerting, and governance to ensure model reliability, fairness, and privacy compliance in production.
  • Optimize models for latency, throughput, and cost across cloud environments (AWS/GCP/Azure).
  • Mentor and grow the AI/ML engineering team; perform code reviews and contribute to architecture decisions.
  • Drive experimentation culture with repeatable experiments, versioning, and rigorous evaluation against business metrics.
  • Partner with product managers and stakeholders to translate business requirements into AI solutions.

Qualification

  • Master’s or PhD in Computer Science, Electrical Engineering, Mathematics, or related field; or equivalent practical experience.
  • 5+ years of hands-on AI/ML engineering experience with production systems.
  • Strong programming skills in Python; experience with PyTorch or TensorFlow (preferably both).
  • Experience with MLOps tools (MLflow, Kubeflow, Seldon) and CI/CD for ML deployments.
  • Proficiency with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Solid foundation in statistics, data structures, algorithms, and model evaluation; strong problem-solving and communication skills.
  • Experience with data pipelines, Spark, SQL, and data processing frameworks.
  • Demonstrated ability to mentor teammates and work effectively with cross-functional teams; track record of delivering impact.

Required Skills

Python PyTorch TensorFlow MLflow Docker Kubernetes AWS GCP Azure SQL Spark Pandas NumPy Git MLOps model deployment monitoring bias mitigation

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