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Data Scientist
Position Overview
We are seeking a pragmatic, results-oriented Data Scientist focused on Applied AI & ML to design, develop, and deploy production-ready machine learning and LLM-powered solutions. The role combines strong ML engineering, LLM and RAG experience, data platform know-how (lakehouse, Azure, Fabric), and business intelligence skills to support analytic products, data-driven decisions, and agent/AI quality. You will partner with cross-functional teams to translate business problems into scalable AI solutions, implement retrieval-augmented generation (RAG) systems, and maintain data pipelines and monitoring for model performance and reliability.
Key Responsibilities
- Design, develop, and deploy machine learning models and LLM-based solutions (including retrieval-augmented generation) to solve business problems and automate decision processes.
- Build and maintain data pipelines and lakehouse integrations on Azure and Microsoft Fabric to ensure reliable data access for training, inference, and BI reporting.
- Implement, evaluate, and optimize LLMs and prompt engineering techniques for production use, including fine-tuning, retrieval strategies, and hybrid retrieval-indexing architectures.
- Collaborate with engineering, product, and analytics teams to define requirements, deliver prototypes, production models, and end-to-end solutions that provide measurable business value.
- Develop tooling and processes for model governance, versioning, monitoring, A/B testing, and agent quality assessment to ensure robust, safe, and auditable AI systems.
- Create and maintain SQL queries, Python scripts, and ETL processes to support feature engineering, training data preparation, and operational inference workloads.
- Deliver BI dashboards and reports (Power BI) and provide data support to stakeholders, translating model outputs into actionable insights and recommendations.
- Optimize model performance and cost across cloud infrastructure, including compute, storage, and inference pipelines on Azure.
- Document solutions, best practices, and runbooks; mentor junior team members and contribute to continuous improvement of AI/ML practices.
Qualifications
- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Engineering, or a related field; PhD preferred but not required.
- 3+ years experience in applied machine learning, data science, or ML engineering, with a track record of delivering production ML or AI solutions.
- Hands-on experience with large language models (LLMs), prompt engineering, fine-tuning, and building retrieval-augmented generation (RAG) systems.
- Strong programming skills in Python and experience writing performant SQL for feature extraction and analysis.
- Experience with cloud platforms preferably Azure and familiarity with Microsoft Fabric, lakehouse architectures, and cloud-native data services.
- Proficiency in BI tools, particularly Power BI, to build dashboards and communicate analytical insights to business stakeholders.
- Experience with model monitoring, A/B testing, model governance, and agent quality evaluation for conversational agents or automated decision systems.
- Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, feature engineering) and MLOps practices.
- Excellent communication skills and ability to work cross-functionally to translate business needs into technical solutions.
- Preferred: experience with additional tools and libraries for LLM deployment (e.g., LangChain, Hugging Face, Azure OpenAI), and familiarity with containerization and CI/CD for ML workflows.
Benefits
- Health
- Dental
- Vision
- 401(k)
- Profit Sharing
- On-Site Fitness Center
- PTO + Floating Holidays
- For this position, you must be currently authorized to work in the United States without the need for sponsorship for a non-immigrant visa. This job was first posted by CyberCoders on 06/10/2026 and applications will be accepted on an ongoing basis until the position is filled or closed.Everforth CyberCoders is proud to be an Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, status as a crime victim, disability, protected veteran status, or any other characteristic protected by law. Our hiring process includes AI screening for keywords and minimum qualifications, and a virtual recruiter as part of the application process. A human recruiter reviews all results. Click here for details on our virtual recruiter . Everforth CyberCoders will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable state and local law, including but not limited to the Los Angeles County Fair Chance Ordinance, the San Francisco Fair Chance Ordinance, and the California Fair Chance Act. Everforth CyberCoders is committed to working with and providing reasonable accommodation to individuals with physical and mental disabilities. Individuals needing special assistance or an accommodation while seeking employment can contact a member of our Human Resources team at Benefits@CyberCoders.com to make arrangements.
