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Member of Technical Staff, Evals and Post-Training

Join Profound as a Post-Training Engineer to enhance AI models for Fortune 500 marketing teams in a fast-paced environment.

Location
New York, New York
Compensation
$230k–$325k/yr
Level
staff
Type
full time · On-site

Posted by employer 1 week ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Apply at Profound → Save job Scanned from tryprofound.com

Skills & Technologies

What you'll build

  • Turn answer-engine data into training datasets
  • Build and iterate on SFT and RL pipelines
  • Design reward signals reflecting customer value
  • Train models for tool use and workflows
  • Prototype new methods on compute and data infrastructure

Must have

  • Exceptional software engineering skills in Python and PyTorch
  • Hands-on post-training experience
  • Experience with distributed training

Nice to have

  • Experience with agentic or tool-use training
  • Experience with retrieval or search-grounded models
  • Publications at venues like NeurIPS or ICML

AI in the day-to-day

Profound’s AI Marketer uses data to automate reporting, draft content, and improve model performance based on real customer interactions.

Not disclosed in this posting: years of experience, visa sponsorship.

Benefits

Equity/Stock Options

Joblaze summary

In the role of Post Training Engineer at Profound, the individual will focus on transforming proprietary answer-engine data into high-quality training datasets and developing models that enhance AI performance for marketing teams. Key skills include proficiency in Python and PyTorch, as well as hands-on experience with reinforcement learning methods and distributed training. This position is suited for someone with a strong software engineering background and a track record of managing projects from inception to deployment. Profound operates in a fast-paced environment, emphasizing rapid iteration and impactful results.

Joblaze insights

  • Listed 11 days ago — first seen on Joblaze October 31, 2026. Last confirmed on Profound's careers page November 10, 2026.
  • Salary band is above the typical range for AI/ML roles (median ~$189,154).
  • Starts above 47% of 88 comparable staff ai/ml roles in United States that list Python we track (median $230,000 across 37 companies). See Python salary trends
  • Python appears in 46.7% of 270 comparable staff ai/ml roles in United States; Slurm appears in 1.1% of 270 comparable staff ai/ml roles in United States.

Quick facts

Is the Member of Technical Staff, Evals and Post-Training role remote?
No — this is an on-site role in New York, New York.
What's the salary range?
Profound lists $230,000–$325,000 for this role.
Where is the role based?
Profound is hiring for this position in New York, New York.
What's the tech stack?
Joblaze extracted these technologies from the posting: JAX, Kubernetes, PyTorch, Python, Slurm.
What seniority level is this role?
Profound targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Member of Technical Staff, Evals and Post-Training role at Profound.

From the original posting

As a Member of Technical Staff in our Evals and Post-training team, you’ll build the evaluation and measurement systems that tell us how good AI (including Profound's harness, known as Aim) is at marketing tasks. These evals guide what we ship, and they are the foundation for our post-training initiatives: the benchmarks, graders, and environments you build become the signal our models are trained against.

What you’ll do

  • Build Profound’s eval system: tasks, rubrics, LLM judges, programmatic verifiers, regression alerts, and self-improvement loops where we look at the traces when something is wrong and come up with the fix

  • Define what a great AI Marketer run looks like, and analyze trajectories across multi-step tool use, analytical correctness, and content quality

  • Work with marketing experts and data labeling companies to define tasks, metrics, rubrics, and other grading mechanisms

  • Close the loop from usage: input use cases, cluster failure modes, and turn these into reliable evals

  • Turn eval results and expert feedback into training signal: rewards, preference data, and training environments

  • Build tooling for debugging model and agent behavior

  • Make evals part of how we decide things: wired into CI, launch reviews, and model selection

Who you are

  • 2+ years building evaluation or measurement systems, whether AI evals, experimentation, ranking, or search quality

  • Strong Python and data skills, with a track record of shipping production systems

  • Deep familiarity with LLM evaluation: LLM-as-judge, benchmark design, agent harnesses, calibration, and understanding how to integrate them into professional settings

  • Sound experimental design, and the instinct to separate signal from noise in non-deterministic systems

  • Familiarity with modern post-training methods: SFT, preference optimization, and RL

  • Strong opinions about how models and agents should behave, and keeping up with current research

  • Comfortable operating in a fast-paced startup environment with rapid iteration cycles

Location

This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact.

For this role, the expected base salary range is $230,000 to $325,000. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.

#LI-PRO

Standard company text repeated across Profound's postings is omitted here.

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