Lead development and execution of company AI strategy, architect scalable AI/ML solutions, manage an AI/ML team, oversee model development and productionization, ensure governance/compliance, partner cross-functionally to deliver measurable AI projects and optimize model performance using MLOps and LLM technologies.
AI Strategy & Leadership
- Develop and execute the company’s AI strategy aligned with business goals and product roadmap.
- Lead cross-functional AI initiatives from concept to deployment, ensuring measurable value.
- Manage and mentor a team of AI/ML professionals, providing technical direction and career development.
- Stay current with emerging AI trends, LLM technologies, and best practices to guide innovation.
Technical Oversight & Architecture
- Architect and design scalable AI/ML solutions, including models, pipelines, and deployment infrastructure.
- Oversee development of machine learning models, including training, evaluation, tuning, and productionization.
- Ensure AI systems meet performance, reliability, security, and compliance requirements.
- Work with engineering teams to integrate AI models into production applications and workflows.
Project Delivery & Collaboration
- Partner with Product, Data, Engineering, and UX teams to identify AI opportunities and translate them into actionable projects.
- Lead technical reviews, roadmap planning, and prioritization for AI initiatives.
- Ensure high-quality documentation for models, datasets, and pipelines.
Data & Model Governance
- Establish best practices for data management, model governance, versioning, monitoring, and ethical AI use.
- Implement processes for model testing, retraining, bias detection, and drift monitoring.
- Ensure adherence to regulatory and compliance standards related to AI and data privacy.
Performance & Optimization
- Analyze performance metrics, user feedback, and business impact to improve AI-driven features.
- Continuously benchmark new tools, frameworks, and LLM technologies for potential adoption.
- Drive experimentation frameworks (A/B testing, reinforcement learning, prompt optimization, etc.) for better model outcomes.
Qualifications Required
- Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, or related field.
- 7–10+ years of experience in AI/ML engineering, data science, or related roles.
- Proven experience leading AI teams or large-scale AI initiatives.
- Strong proficiency in Python, machine learning frameworks (TensorFlow, PyTorch, Sklearn), and data engineering tools.
- Experience with LLMs, generative AI, and prompt engineering.
- Hands-on experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (Kubeflow, MLflow, SageMaker).
- Strong understanding of data structures, algorithms, model optimization, and deployment best practices.
Preferred
- Experience building conversational AI, recommendation engines, predictive analytics, or intelligent automation systems.
- Familiarity with vector databases, embeddings, retrieval-augmented generation (RAG), and LLM fine-tuning.
- Experience with distributed computing frameworks (Spark, Ray).
- Certifications in AI/ML, cloud, or data engineering.
- Strong understanding of responsible AI, fairness, and regulatory requirements
Compensation, Benefits and Duration
Minimum Compensation: USD 54,000
Maximum Compensation: USD 189,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
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