ZEFR

Senior Data Scientist

ZEFR$200K — $225K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Computer Science or related field with 4+ years in machine learning or data science
  • Hands-on experience fine-tuning large language models
  • Experience with LLM inference optimization techniques
  • Proven track record of deploying ML models at scale
  • Fluency in Python and SQL, particularly with Snowflake
  • Experience with multimodal models and features
  • Familiarity with cost/quality analysis of LLMs

Responsibilities

  • Research and prototype large language models for social media content understanding
  • Fine-tune and optimize LLMs for various modalities
  • Deploy LLMs for high-quality production environments
  • Build scalable AI systems that integrate multiple models
  • Perform inference optimizations balancing quality, latency, and cost
  • Manage the full lifecycle of LLMs from research to production-grade deployments
  • Collaborate actively with team members to push LLM capabilities

Benefits

  • Flexible PTO
  • Comprehensive medical, dental, and vision insurance with FSA options
  • Company-paid life insurance
  • Paid parental leave
  • 401(k) with company match
  • Professional development opportunities
  • 13 paid holidays off
  • Options for in-office, hybrid, or fully-remote work
  • Summer Fridays for shorter workdays in summer
  • In-office lunches and plenty of free food
  • Optional events to celebrate team milestones
Full Job Description
What you'll do:

We are hiring a Senior Data Scientist focused on the research and productionalization of Large Language Models for multimodal social media content understanding. We work with multi-terabytes of social media platform data from TikTok, YouTube, Facebook, Instagram, and Snap. In this role you will fine-tune, optimize, and deploy LLMs that understand what hundreds of millions of videos, images, and text posts are about.

Your work will span the full lifecycle - from research and prototyping to production-grade serving at scale. You will fine-tune LLMs and perform inference optimizations, balancing quality, latency and cost. You will build sophisticated compound AI systems that combine multiple models and modalities into reliable, scalable pipelines.

We are excited to welcome someone who is passionate about pushing the boundaries of what LLMs can do and who can keep up with the rapidly evolving landscape of foundation models and inference infrastructure. 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
  • Data Processing: Ray, Pandas, DBT, FastAPI, Airflow, Astronomer, DBOS
  • DevOps: Github Actions, Docker, Terraform, Kubernetes, ArgoCD, AWS, GCP, Datadog
  • MLOps & Inference: PyTorch, Triton Inference Server, vLLM, Nvidia Dynamo, Nvidia TensorRT LLM, Weights and Biases, Transformers, ONNX, Nvidia TensorRT, DVC, HuggingFace, CUDA, Baseten Inference
  • Tools: Voxel51, Claude Code, Cursor

What we're looking for:
  • Bachelor's or Master's degree in Computer Science or related field with 4+ years of professional experience in machine learning or data science
  • Hands-on experience fine-tuning large language models (open-source and/or closed-source)
  • Experience with LLM inference optimization - KV cache management, quantization, multi-node GPU serving, batching strategies, and serving frameworks (vLLM, TensorRT LLM, SGLang)
  • Track record of taking ML models from research to production at scale
  • Fluency with Python and SQL (specifically Snowflake)
  • Experience working with multimodal models and features
  • Familiarity with cost/quality tradeoff analysis across LLM providers and self-hosted models
  • Experience with distributed systems and GPU-accelerated workloads
  • Strong foundation in data structures, algorithms, and software design
  • Thorough testing and code review standards/practices
  • Strong verbal and written communication skills
  • Experience working with Autonomous Coding Agents
  • Openness to new technologies and creative solutions


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
  • 13 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 $200,000 and $225,000. 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.

About ZEFR

ZEFR is a technology company that provides contextual targeting solutions for brands. The company's platform offers a suite of software tools that enable brands to identify and target their desired audiences on YouTube and other social media platforms. ZEFR's technology uses machine learning algorithms to analyze video content and identify relevant keywords and topics, which can then be used to target specific audiences with relevant ads. The company was founded in 2009 and is headquartered in Burbank, California.
Learn more about ZEFR
Size
200 employees
Industry
Founded
2008

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