Databricks

5 months ago

Staff Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 12 hours agoStatus: Live

Job Summary

Join the Applied AI team to shape GenAI products by building and tuning AI models, data pipelines, and scalable backend systems across Databricks’ suite (Databricks Assistant, AI/BI Genie). Collaborate with researchers and product teams to improve LLM quality and user experiences, deploying end-to-end models from research through production at scale.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Shape the direction of our applied AI areas and intelligence features in our products. Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie).
•Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains.
•Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.
•Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction.
•Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model performance.

Key Requirements

•2-8 years of machine learning engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML research in academia will be considered as an equivalent qualification.
•Strong track record of working with language modeling technologies, including generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, and evaluation benchmarks.
•Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures.
•Ability to drive end-to-end model development, from research and prototyping to deployment and monitoring.
•Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences.

Experience:AISaaSCloud

Skills:Problem-solvingCommunicationCollaboration

Languages:English

Tech Stack:PythonTensorFlowPyTorchLLMRAG

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Databricks

5 months ago

Staff Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 12 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Shape the direction of our applied AI areas and intelligence features in our products. Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie).
•Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains.
•Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.
•Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction.
•Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model performance.

Key Requirements

•2-8 years of machine learning engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML research in academia will be considered as an equivalent qualification.
•Strong track record of working with language modeling technologies, including generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, and evaluation benchmarks.
•Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures.
•Ability to drive end-to-end model development, from research and prototyping to deployment and monitoring.
•Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences.

Experience:AISaaSCloud

Skills:Problem-solvingCommunicationCollaboration

Languages:English

Tech Stack:PythonTensorFlowPyTorchLLMRAG

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn