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Freelance Machine Learning Engineer Jobs in Springfield, OR

Bespoke Labs

Machine Learning Engineer

Eugene, OR

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

Eugene, OR · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

DataAnnotation

SDLC Engineer - AI Trainer

Eugene, OR · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Eugene, OR · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

Varsity Tutors

Data Science Tutor

Eugene, OR · Remote

$40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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All JobsFreelance Machine Learning Engineer JobsFreelance Machine Learning Engineer Jobs in Springfield, OR

Freelance Machine Learning Engineer information

See Springfield, OR salary details

$14

$45

$125

How much do freelance machine learning engineer jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for freelance machine learning engineer in Springfield, OR is $45.26, according to ZipRecruiter salary data. Most workers in this role earn between $23.03 and $58.61 per hour, depending on experience, location, and employer.

What does a Freelance Machine Learning Engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Engineer, and why are they important?

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

What is the difference between Freelance Machine Learning Engineer vs Data Scientist?

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

What are popular job titles related to Freelance Machine Learning Engineer jobs in Springfield, OR? For Freelance Machine Learning Engineer jobs in Springfield, OR, the most frequently searched job titles are:
Freelance Machine Learning Engineer jobs near you
Infographic showing various Freelance Machine Learning Engineer job openings in Springfield, OR as of June 2026, with employment types broken down into 77% Full Time, and 23% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $94,138 per year, or $45.3 per hour.

Machine Learning Engineer

Bespoke Labs

Eugene, OR

Full-time

Posted 3 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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