Machine Learning Engineer

job
  • ZEFR
Job Summary
Location
Marina del Rey ,CA 90292
Job Type
Contract
Visa
Any Valid Visa
Salary
PayRate
Qualification
BCA
Experience
2Years - 10Years
Posted
19 Dec 2024
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Job Description
What we do:

Zefr is the global leader in brand suitability targeting and measurement across the world's largest platforms. Zefr's technology is helping to power the age of responsible marketing by putting advertisers in control of their content adjacencies based on their own unique brand safety and suitability preferences, mapped to the Global Alliance of Responsible Media's (GARM) industry standards. As an official YouTube Measurement Program Partner, Meta for Business Partner, and TikTok for Business Partner, the company leverages patented machine learning and AI technology (Cognition AI) to offer brands and agencies more precise and transparent brand safety and suitability activation and measurement solutions on scaled platforms. The company is headquartered in Los Angeles, California, with additional locations across the globe.
What you'll do:

We are hiring a Machine Learning Engineer to be involved in designing and building large-scale applications and systems to acquire, process, and store multi-terabytes of YouTube, TikTok, Facebook and other social media data. In this role you will implement machine learning infrastructure to understand what hundreds of millions of videos are about. You will be working with state of the art models, including large language models, to build sophisticated compound AI systems. We are excited to welcome someone who is passionate about cutting edge research in machine learning and computer vision. We want an individual who can keep up to date with the ever-expanding field of Machine Learning Operations.

This is a role where we both expect to learn from you and have you learn from us!

Tech stack:
  • Languages: Python, SQL
  • Data Stores: Snowflake, Qdrant, OpenSearch, DynamoDB
  • Data Processing: Apache Kafka, Pandas, DBT, FastAPI
  • DevOps: Github Actions, Docker, Terraform, Kubernetes, ArgoCD, AWS, GCP, Datadog
  • MLOps: Triton Inference Server, Weights and Biases, Transformers, Onnx, TensorRT, DVC, HuggingFace
What we're looking for:
  • Bachelor's or Master's degree in Computer Science or related field with 2+ years of professional experience
  • Machine Learning Operations
  • Data Engineering
  • Fluency with Python and SQL (Specifically Snowflake)
  • Experience with distributed systems and machine learning models
  • Experience with working with Large language models and RAG systems
  • Strong foundation in data structures, algorithms and software design
  • Thorough testing and code review standards/practices
  • Strong verbal and written communication skills
  • Openness to new technologies and creative solutions
  • Preference for a candidate that is located in (or willing to relocate to) the great Los Angeles area

Zefr is an equal opportunity employer that embraces diversity and inclusion in the workplace. We are committed to building a team that represents a variety of backgrounds, skills, and perspectives because we know this only makes us better. We strongly encourage women, persons of color, LGBTQIA+ individuals, persons with disabilities, members of ethnic minorities, foreign-born residents, and veterans to apply even if you do not meet 100% of the qualifications.
Benefits (for US based employees):
  • Flexible PTO
  • Medical, dental, and vision insurance with FSA options
  • Company-paid life insurance
  • Paid parental leave
  • 401(k) with company match
  • Professional development opportunities
  • 14 paid holidays off
  • In-office, hybrid, and fully-remote work options available
  • "Summer Fridays" (shorter work days on select Fridays during the summertime)
  • In-office lunches and lots of free food
  • Optional in-person and virtual events (we like to celebrate!)
Compensation (for US based employees):

The anticipated base salary for this position is between $130,000 to $160,000. Within the range, individual pay is determined by factors such as job-related skills, experience, and relevant education or training. If your compensation expectations fall outside of this range, it may still be worth having a conversation.
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