Full-Time

GenAI Senior 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

$166k - $225kAnnually

+ Annual Performance Bonus + Equity

Senior

San Francisco, CA, USA

Category
Applied Machine Learning
Deep Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Machine Learning

You match the following Databricks's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • 5+ years of full time industry experience
  • Strong software engineering skills
  • Experience building large-scale distributed systems
  • Experience building ML platform systems for applications in the ML model development lifecycle such as model training, data preparation, model evaluation, and model serving
  • Strong sense of end-to-end product ownership as well as intuition for both robust system design and product usability
  • Effective communication skills and the ability to articulate complex technical ideas to cross-disciplinary internal and external stakeholders.
Responsibilities
  • Play a key role in the end-to-end design and implementation of our product which is a platform for powering use cases across training and serving of generative AI models
  • Work closely with both ML researchers in the company and customers to identify key areas of development for our generative AI platform
  • Have strong end-to-end product ownership, translating product requirements into user interfaces and backend distributed system design as well as own the implementation of these designs
  • Design and build the core platform infrastructure that supports our customer-facing product features
  • Ensure the reliability, security, and scalability of the backend distributed systems that power all aspects of our product.
Desired Qualifications
  • Direct experience developing ML models is a plus but not required

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. The company operates on a subscription-based model, generating revenue from platform access and professional services. Databricks aims to simplify data management and analytics for its users.

Company Stage

Debt Financing

Total Funding

$13.6B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

0%

1 year growth

1%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Databricks raised $15 billion for AI product development and global expansion.
  • The acquisition of BladeBridge enhances Databricks' capabilities in automated data migration.
  • Increased demand for real-time analytics boosts adoption of Databricks' platform.

What critics are saying

  • Increased competition from Snowflake challenges Databricks' lakehouse architecture.
  • Integration challenges from BladeBridge acquisition may disrupt workflows and delay rollouts.
  • Reliance on large-scale debt financing poses financial risks if market conditions change.

What makes Databricks unique

  • Databricks' lakehouse architecture combines data lakes and warehouses for efficient data management.
  • The platform supports collaborative data science and machine learning workflows, enhancing team productivity.
  • Databricks integrates seamlessly with various cloud services, supporting multi-cloud strategies.

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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