Full-Time

GenAI Senior Staff Machine Learning Engineer

Platform

Confirmed live in the last 24 hours

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Compensation Overview

$232k - $313kAnnually

+ Annual Performance Bonus + Equity

Senior, Expert

San Francisco, CA, USA

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Python
Go
C/C++
Requirements
  • 8+ years of hands-on programming experience with at least one modern language such as Python, Go, or C++
  • 8+ years of experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools
  • Strong sense of software design and usability of ML systems
  • Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security.
  • Prior experience in developing public cloud services or open source ML software is an advantage.
Responsibilities
  • Serve as a technical lead, overseeing and supervising projects and engineers on the team.
  • Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies
  • Drive our technology vision and roadmap
  • Establish software development best practices, and lead by example in applying them
  • Develop our engineering organization and culture through hiring, mentoring, and feedback.

Databricks provides a platform that combines the features of data lakes and data warehouses, referred to as lakehouse architecture. This platform allows organizations to efficiently manage, analyze, and gain insights from their data. It caters to a diverse clientele, including data engineers, data scientists, and business analysts in sectors like finance, healthcare, and technology. Databricks streamlines data ingestion, management, and analysis through automated ETL processes, secure data sharing, and high-performance analytics. Additionally, it supports machine learning and AI workloads, enabling users to build and deploy models at scale. Unlike many competitors, Databricks operates on a subscription-based model, generating revenue through platform access and professional services. The company's goal is to empower organizations to leverage their data effectively for better decision-making and insights.

Company Stage

Growth Equity (Venture Capital)

Total Funding

$13.6B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

0%

1 year growth

3%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Databricks raised $10B, boosting its valuation to $62B for global expansion.
  • The company reports a $3B revenue run rate, indicating strong financial performance.
  • Databricks' expansion into Saudi Arabia aligns with Vision 2030, enhancing Middle East presence.

What critics are saying

  • Increased competition from Snowflake could impact Databricks' market share.
  • Integration challenges with acquisitions like Tabular may disrupt operations.
  • Expansion into new markets may expose Databricks to geopolitical and regulatory risks.

What makes Databricks unique

  • Databricks offers a unified platform combining data lakes and warehouses, known as lakehouse.
  • The platform supports collaborative data science and machine learning workflows efficiently.
  • Databricks integrates seamlessly with various cloud services for enhanced data management.

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Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave