> Markdown version of [/jobs/ext/4324444-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/4324444-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** Spark Tek Inc - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Engineering, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), Machine Learning, NumPy, Performance Tuning, Azure Machine Learning, Software Engineering, SQL Databases, Snowflake, Fastapi, Pandas, Information Technology, Machine Learning Operations, Restful APIs, Data Pipelines, Docker, Databricks, Microservices - **Published:** October 31, 2026 - **Apply:** https://www.juju.com/job/15_63507b22 ## About the Role * Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or equivalent field, with strong communication and cross-functional collaboration skills. * Bachelor's degree in a technical field such as computer science, computer engineering or related field required * 5 years of experience as AI/ML Engineer * Ability to work as part of a team and collaborate, as well as work independently or with minimal direction * Excellent written, presentation, and verbal communication skills * Experience in Machine Learning, Data Engineering, ML Infrastructure, or related fields, with strong foundations in probability, statistics, and machine learning. * Hands-on experience with Databricks, including Unity Catalog, and cloud ML platforms such as Azure ML Studio, AWS, or GCP. * Experience building and scaling end-to-end ML systems, ETL/ELT pipelines, and data workflows using Python, NumPy, Pandas, and SQL. * Experience building scalable APIs and microservices using FastAPI, with Snowflake or equivalent data warehouse technologies. * Experience deploying production workloads using Docker and Kubernetes, with a strong understanding of scalable, reliable software engineering practices. ## Description * Design and develop scalable ML models and workloads on cloud ML platforms such as Azure ML Studio, AWS, or GCP * Facilitate and participate in the preparation of ML models and their scoring processes * Develop and support the ML portion of the DT GoToMarket strategy to maximize the distribution of ML predictions and recommendations, including publish microservices/APIs * Incorporate workflows into ML Model Engineering processes, to automate, monitor, and produce alerts * Implement performance tuning and model optimization * Stay current on emerging ML platforms and technologies and recommend solutions that would enhance current systems or implementation * Collaborate with Product and Engineering team members to follow all documented architecture, design & deployment processes to ensure compliance with policies *