Lead development of a generative AI proof-of-concept and integrate AI solutions into software workflows. Mentor data engineers, design and implement Python-based generative AI applications, build scalable data pipelines, deploy models/APIs, and translate stakeholder requirements into technical solutions while staying current on AI and data engineering best practices.
Key Responsibilities:
- Lead the creation of a POC for using generative AI in software development, demonstrating its potential to improve efficiency, quality, and innovation.
- Collaborate with software development teams to integrate generative AI solutions into existing workflows.
- Lead and mentor a team of data engineers, providing technical guidance and fostering a collaborative team environment.
- Design, develop, and implement generative AI applications using Python.
- Work closely with stakeholders to understand business requirements and translate them into technical solutions.
- Drive the development and execution of data engineering strategies to support business objectives.
- Develop and maintain scalable data pipelines, API and model deployments, and workflows.
- Communicate complex analytical findings and insights to non-technical stakeholders in a clear and concise manner.
- Stay current with industry trends, best practices, and emerging technologies in data analytics, generative AI, and Python programming.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- 5+ years of experience in data engineering and AI, with at least 2 years in a leadership or supervisory role.
- Proficiency in Python programming and its libraries (e.g. pandas, numpy, scikit-learn, matplotlib, seaborn).
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data analytics and AI services.
- Strong understanding of statistical analysis, machine learning, and data mining techniques.
- Experience with generative AI models (e.g., GPT, GANs) and their applications in software development.
- Experience with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI) is a plus.
- Solid experience with SQL and database management.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication and interpersonal skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
Preferred Qualifications:
- Knowledge of data governance and data privacy regulations.
- Experience in agile development methodologies.
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What you need to know about the Los Angeles Tech Scene
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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- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
