Oscar
Base pay range: $225,000 - $275,000 per year
Location:
San Francisco, California (Remote) Job Type:
Full-Time
About Us We are a rapidly growing technology company at the forefront of AI‑driven data intelligence and analytics. Our platform empowers organizations across multiple industries to unlock the full potential of their data through advanced machine learning, predictive analytics, and intelligent automation. We serve clients in biotech, fintech, healthcare, energy, real estate, and enterprise technology sectors.
The Role We’re looking for a Lead AI Engineer to architect and deploy production‑grade AI/ML systems that solve real business problems. You’ll lead technical initiatives, build scalable infrastructure, mentor a team, and stay hands‑on with code. This is not about building demos – it’s about shipping models that work at scale and drive measurable business impact.
What You’ll Do Build & Architect
Design and implement scalable AI/ML infrastructure and pipelines from the ground up
Develop production machine learning models for data classification, predictive analytics, and anomaly detection
Build NLP systems for unstructured data analysis and intelligent automation
Create robust MLOps workflows for continuous training, deployment, and monitoring
Lead & Mentor
Lead a team of AI/ML engineers and data scientists
Set technical direction and establish best practices for the team
Conduct code reviews and provide hands‑on guidance on complex problems
Foster a culture of experimentation, learning, and shipping fast
Ship & Scale
Deploy models to production with proper monitoring, logging, and alerting
Optimize performance, latency, and resource utilization at scale
Implement CI/CD practices for ML systems
Work cross‑functionally with product, engineering, and data teams
Innovate
Stay current with AI/ML research and evaluate new techniques
Prototype and validate emerging technologies (LLMs, generative AI, etc.)
Drive innovation in how we leverage AI for data intelligence
Contribute to technical discussions and strategy
You Have Required Qualifications
8+ years of hands‑on experience building and deploying AI/ML systems in production
3+ years leading technical projects or teams
Deep expertise with modern ML frameworks (PyTorch, TensorFlow, scikit‑learn)
Strong Python skills and software engineering fundamentals
Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
Proven track record shipping ML models that handle real‑world scale and complexity
Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
Bonus Points
Master’s or PhD in ML/AI or related field
Experience with LLMs, generative AI, or foundation models
Background in MLOps tools (MLflow, Kubeflow, SageMaker)
Knowledge of data governance or privacy‑preserving ML
Experience in fintech, healthcare tech, or data platforms
Open‑source contributions or publications
Compensation & Benefits
Base salary: $225,000 – $275,000
Equity package
Comprehensive health, dental, and vision insurance
401(k) with company match
Flexible PTO policy
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Location:
San Francisco, California (Remote) Job Type:
Full-Time
About Us We are a rapidly growing technology company at the forefront of AI‑driven data intelligence and analytics. Our platform empowers organizations across multiple industries to unlock the full potential of their data through advanced machine learning, predictive analytics, and intelligent automation. We serve clients in biotech, fintech, healthcare, energy, real estate, and enterprise technology sectors.
The Role We’re looking for a Lead AI Engineer to architect and deploy production‑grade AI/ML systems that solve real business problems. You’ll lead technical initiatives, build scalable infrastructure, mentor a team, and stay hands‑on with code. This is not about building demos – it’s about shipping models that work at scale and drive measurable business impact.
What You’ll Do Build & Architect
Design and implement scalable AI/ML infrastructure and pipelines from the ground up
Develop production machine learning models for data classification, predictive analytics, and anomaly detection
Build NLP systems for unstructured data analysis and intelligent automation
Create robust MLOps workflows for continuous training, deployment, and monitoring
Lead & Mentor
Lead a team of AI/ML engineers and data scientists
Set technical direction and establish best practices for the team
Conduct code reviews and provide hands‑on guidance on complex problems
Foster a culture of experimentation, learning, and shipping fast
Ship & Scale
Deploy models to production with proper monitoring, logging, and alerting
Optimize performance, latency, and resource utilization at scale
Implement CI/CD practices for ML systems
Work cross‑functionally with product, engineering, and data teams
Innovate
Stay current with AI/ML research and evaluate new techniques
Prototype and validate emerging technologies (LLMs, generative AI, etc.)
Drive innovation in how we leverage AI for data intelligence
Contribute to technical discussions and strategy
You Have Required Qualifications
8+ years of hands‑on experience building and deploying AI/ML systems in production
3+ years leading technical projects or teams
Deep expertise with modern ML frameworks (PyTorch, TensorFlow, scikit‑learn)
Strong Python skills and software engineering fundamentals
Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
Proven track record shipping ML models that handle real‑world scale and complexity
Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
Bonus Points
Master’s or PhD in ML/AI or related field
Experience with LLMs, generative AI, or foundation models
Background in MLOps tools (MLflow, Kubeflow, SageMaker)
Knowledge of data governance or privacy‑preserving ML
Experience in fintech, healthcare tech, or data platforms
Open‑source contributions or publications
Compensation & Benefits
Base salary: $225,000 – $275,000
Equity package
Comprehensive health, dental, and vision insurance
401(k) with company match
Flexible PTO policy
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