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Contract Google Machine Learning Engineer Jobs in Frederick, MD

Bespoke Labs

Machine Learning Engineer

Hagerstown, MD · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Frederick, MD · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Varsity Tutors

Machine Learning Tutor

Leesburg, VA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

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How much do contract google machine learning engineer jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for contract google machine learning engineer in Frederick, MD is $48.65, according to ZipRecruiter salary data. Most workers in this role earn between $40.87 and $50.43 per hour, depending on experience, location, and employer.
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Contract Google Machine Learning Engineer jobs near you
Infographic showing various Contract Google Machine Learning Engineer job openings in Frederick, MD as of June 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $101,198 per year, or $48.7 per hour.

Machine Learning Engineer

Bespoke Labs

Gaithersburg, MD • On-site

Full-time

Posted 10 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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