ML Engineer-Databricks
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Before you apply
SalaryNo pay range posted
LocationSan Jose, CA
Typefull-time
SenioritySenior
Experience5+ yrs
EquityIncluded
Company size1,001–5,000 people
PostedOct 28, 2026 · 1w ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or equivalent field
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
Skills
Databricks
Unity Catalog
Azure ML Studio
AWS
GCP
Python
NumPy
Pandas
SQL
FastAPI
Snowflake
Docker
Kubernetes
ML Engineer-Databricks1
Responsibilities
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Design and develop scalable ML models and workloads on cloud ML platforms such as Azure ML Studio, AWS, or GCP.
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Facilitate and participate in the preparation of ML models and their scoring processes
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Develop and support the ML portion of the DT GoToMarket strategy to maximize the distribution of ML predictions and recommendations, including publish microservices/APIs
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Incorporate workflows into ML Model Engineering processes, to automate, monitor, and produce alerts
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Implement performance tuning and model optimization
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Stay current on emerging ML platforms and technologies and recommend solutions that would enhance current systems or implementationCollaborate with Product and Engineering team members to follow all documented architecture, design & deployment processes to ensure compliance with policies
Skills & background:
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Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or equivalent field, with strong communication and cross-functional collaboration skills.
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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.
Legal
Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additional compensation may include benefits, discretionary bonuses, and equity