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AI/Machine Learning EngineerVarite • United States
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AI/Machine Learning Engineer

Varite
  • US
    United States
  • US
    United States
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Über

About the Role We are looking for an
Evaluation Scientist
who can work across both
hands-on experimentation
and
automation infrastructure . This role begins with running
manual evaluations
(e.g., executing and monitoring individual experiments) and progresses toward building
scripts, tools, and infrastructure
that streamline and automate these processes, with the long-term goal of reducing manual work as much as possible. The ideal candidate will also bring expertise in
coding agents
and
quality evaluation , enabling them to design robust experiments and improve workflows. While the role will receive high-level guidance, candidates should be able to
independently define and implement the lower-level details
of experiment setup after ramping up. For example, given a high-level requirement for a new type of evaluation, the candidate should be able to
propose and execute an implementation plan
with detailed steps, metrics, and automation in place. Key Responsibilities
Run and manage
manual evaluation experiments
across AI/ML systems. Develop and maintain
automation infrastructure
(scripts, pipelines, tools) to reduce manual evaluation work. Design and execute
new types of evaluations , translating broad research questions into structured experiment setups. Work with
coding agents
and applied ML workflows to define and measure quality. Define
metrics, benchmarks, and evaluation criteria
to assess performance and identify gaps. Collaborate with research leads to align evaluation design with project goals while owning
implementation details . Ensure reproducibility, consistency, and scalability of evaluation processes. Qualifications
Strong coding skills in
Python
(or equivalent) for scripting, automation, and experiment design. Experience with
running and analyzing experiments , including quality evaluation methodologies. Knowledge of
coding agents, ML models, or applied automation frameworks . Ability to
work independently : take high-level requirements and define detailed steps for execution. 2-4 years of hands-on experience in
evaluation, scripting, or applied data science/ML
(academic or industry). Strong analytical skills with experience in
data handling, reporting, and experiment analysis . Preferred Skills
Familiarity with
evaluation frameworks
and automation tools in AI/ML research. Experience in
building scalable infrastructure
for experiments or evaluations. Knowledge of
experimental design, statistical testing, or quality benchmarking .
  • United States

Sprachkenntnisse

  • English
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