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Contract Machine Learning Engineer Jobs in Albuquerque, NM

Varsity Tutors

Machine Learning Tutor

Albuquerque, NM · 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 ...

Varsity Tutors

Data Science Tutor

Albuquerque, NM · Remote

$18 - $40/hr

... machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

Varsity Tutors

Python Tutor

Albuquerque, NM · Remote

$18 - $40/hr

... Python to machine learning, web scraping, scientific computing, and DevOps applications ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

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All JobsContract Machine Learning Engineer JobsContract Machine Learning Engineer Jobs in Albuquerque, NM

Contract Machine Learning Engineer information

See Albuquerque, NM salary details

$30.5K

$124.8K

$187.5K

How much do contract machine learning engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for contract machine learning engineer in Albuquerque, NM is $124,803.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,400.00 and $150,200.00 per year, depending on experience, location, and employer.

What is a Contract Machine Learning Engineer job?

A Contract Machine Learning Engineer is a professional who builds and deploys machine learning models on a temporary or project-based basis. They typically work with companies seeking specialized expertise in data science, model development, or AI integration without committing to a full-time hire. Responsibilities may include data preprocessing, model training, algorithm optimization, and deployment. Contract roles allow for flexibility and are often remote, making them ideal for businesses with short-term AI needs or startups looking to scale their machine learning capabilities quickly.

What are the typical day-to-day responsibilities of a Contract Machine Learning Engineer?

As a Contract Machine Learning Engineer, your daily tasks usually involve gathering and preprocessing data, building and fine-tuning machine learning models, and collaborating with software engineers and product managers to integrate your models into production systems. You may also meet with clients or internal teams to gather requirements and provide technical insights, as well as document and present your findings to stakeholders. Work is typically project-based and may require a high degree of independence, flexibility, and adaptability. This dynamic environment often exposes you to a variety of industries and technical challenges, making each project unique and providing valuable experience for professional growth.

What are the key skills and qualifications needed to thrive in the Contract Machine Learning Engineer position, and why are they important?

To thrive as a Contract Machine Learning Engineer, you need a strong background in machine learning algorithms, data preprocessing, statistical analysis, and proficiency in programming languages such as Python or R, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms (AWS, Google Cloud, Azure) or certifications in these areas are common requirements. Excellent problem-solving, communication, and time management skills are vital, especially when working with cross-functional teams and managing multiple projects remotely. These skills ensure effective delivery of high-quality, scalable machine learning solutions within tight project timelines and diverse client environments.

What are the most commonly searched types of Machine Learning Engineer jobs in Albuquerque, NM? The most popular types of Machine Learning Engineer jobs in Albuquerque, NM are:
What are popular job titles related to Contract Machine Learning Engineer jobs in Albuquerque, NM? For Contract Machine Learning Engineer jobs in Albuquerque, NM, the most frequently searched job titles are:
What job categories do people searching Contract Machine Learning Engineer jobs in Albuquerque, NM look for? The top searched job categories for Contract Machine Learning Engineer jobs in Albuquerque, NM are:
Contract Machine Learning Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Albuquerque, NM • On-site

Full-time

Posted 8 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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