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Full Stack Machine Learning Engineer Jobs in Columbus, OH

Machine Learning Engineer, Perception

Columbus, OH · On-site +1

$100.90K - $138.60K/yr

... learning, and Python programming to tackle challenges in our field alongside our talented teams. What You'll Do Experienced: * Implement, validate, and iterate on machine learning algorithms for weld ...

Full Stack Developer Position Responsibilities Full Stack Developer Columbus , OH - 299149 (Need nearby Candidates) MUST have skills: Java, Microservices, Restful, Spring, Spring boot, Batch, Kafka ...

Experienced full stack software engineer who has a track record of designing & launching apps (for ... Enthusiasm for keeping current with advances in AI and machine learning, with the ability to ...

Full Stack Platform Engineer Client is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across ...

New

As a Full Stack Software Engineer, you will create and support features on their platform, focusing on building dynamic data visualization components and scalable APIs. Responsibilities : • Build ...

As a Full Stack Software Engineer, you will create and support features on their platform, focusing on building dynamic data presentation features and collaborating with various teams to enhance user ...

Java Full Stack Developer

Columbus, OH · On-site

$50.75 - $65.50/hr

Java Full Stack Developer Job Location: Columbus, OH Job Type: Contract : * Java Full Stack ... Software Engineer should have general development skills, mainly in Java and JavaScript * General ...

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Full Stack Machine Learning Engineer information

See Columbus, OH salary details

$43K

$130.2K

$184K

How much do full stack machine learning engineer jobs pay per year?

As of Jun 3, 2026, the average yearly pay for full stack machine learning engineer in Columbus, OH is $130,175.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,200.00 and $152,600.00 per year, depending on experience, location, and employer.

What is a Full Stack Machine Learning Engineer job?

A Full Stack Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models into production. They work across the entire ML pipeline, from data collection and preprocessing to model training, evaluation, and deployment using backend and frontend technologies. This role requires expertise in software engineering, data engineering, and machine learning frameworks like TensorFlow or PyTorch. Additionally, they ensure scalability, reliability, and maintainability of ML systems in real-world applications.

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

To thrive as a Full Stack Machine Learning Engineer, you need robust programming skills (Python, JavaScript), a deep understanding of machine learning algorithms, and experience with both backend and frontend development. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, Azure, GCP), and tools such as Docker and Kubernetes, as well as relevant certifications, are highly beneficial. Strong problem-solving abilities, effective communication, and a collaborative mindset are essential soft skills for working across interdisciplinary teams. These competencies are crucial to designing, deploying, and scaling machine learning solutions in production environments while ensuring seamless integration from data to user interface.

What are some typical challenges Full Stack Machine Learning Engineers face, and how do they overcome them?

Full Stack Machine Learning Engineers often encounter challenges such as integrating complex machine learning models into scalable and maintainable production systems, and ensuring efficiency across both backend and frontend components. They must address issues like managing large and varied datasets, optimizing model inference times, and adapting to fast-evolving technologies. Overcoming these hurdles often requires close collaboration with data scientists, DevOps professionals, and product teams, as well as staying updated with best practices in MLOps and system architecture. Being proactive in learning new tools and fostering effective communication are key strategies for success in this dynamic role.
What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Columbus, OH? The most popular types of Full Stack Machine Learning Engineer jobs in Columbus, OH are:
What are popular job titles related to Full Stack Machine Learning Engineer jobs in Columbus, OH? For Full Stack Machine Learning Engineer jobs in Columbus, OH, the most frequently searched job titles are:
What job categories do people searching Full Stack Machine Learning Engineer jobs in Columbus, OH look for? The top searched job categories for Full Stack Machine Learning Engineer jobs in Columbus, OH are:
Principal Machine Learning Engineer

Principal Machine Learning Engineer

UpStart

Columbus, OH • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

About Upstart Upstart is the leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than 80% of borrowers are approved instantly, with zero documentation to upload.

Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas. Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk.

If you are energized by the impact you can make at Upstart, we'd love to hear from you! The Team Upstart's Decisioning org is forming a new, high-leverage Applied Machine Learning team to push the boundaries of model accuracy in our underwriting systems. Reporting directly to the Director and org leader, you'll be the founding member of this team, which serves as the applied ML counterpart to our centralized ML Science group.

This team is chartered to drive model precision by focusing on feature engineering, model tuning, embedding optimization, and CUDA-accelerated training workflows. You'll be working at the intersection of engineering and data science to drive improvements that have direct business impact on pricing accuracy and borrower conversion. How You'll Make an Impact Serve as the technical lead for applied ML initiatives that improve the accuracy, precision, and recall of underwriting models.

Design and implement advanced ML training strategies, including AutoML, ensemble learning, and temporal modeling techniques. Drive GPU-accelerated experimentation, including CUDA-based training optimization and embedding fine-tuning. Build robust data preprocessing and feature engineering pipelines that can be used in both experimentation and production.

Influence modeling strategy through close collaboration with Pricing Engineering and the ML Science organization. Deliver measurable improvements to model-driven business outcomes such as conversion rate, rate accuracy, and loan performance. Mentor future applied ML engineers and help define the long-term roadmap for ML excellence within Pricing.

Minimum Qualifications 8+ years of hands‐on experience in applied machine learning, with strong exposure to production‐scale modeling efforts. Proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, Scikit‐learn, XGBoost). Demonstrated expertise in end‐to‐end model development: data prep, feature engineering, training, evaluation, and deployment.

Practical experience optimizing ML workflows using CUDA/GPU acceleration. Strong grasp of regression and classification metrics (e.g., precision, recall, R2, MPVRMSE) and how to apply them to production models. Ability to work autonomously and lead technical direction in ambiguous, high‐impact domains.

Preferred Qualifications Experience working in high‐scale, ML‐driven product environments—especially in fintech, pricing, or risk modeling. Background in feature store design, embedding architecture, or synthetic data generation for model training. Proven track record of improving model accuracy in production environments with measurable business outcomes.

Ability to bridge engineering and science teams, and influence technical strategy across disciplines. Familiarity with modern experimentation frameworks, hyperparameter tuning tools, and automated model selection techniques. Position location This role is available in the following locations: Remote Travel requirements As a digital first company, the majority of your work can be accomplished remotely.

The majority of our employees can live and work anywhere in the U.S but are encouraged to still spend high quality time in‐person collaborating via regular onsites. The in‐person sessions' cadence varies depending on the team and role; most teams meet once or twice per quarter for 2‐4 consecutive days at a time. What you'll love: Competitive Compensation (base + bonus & equity) Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart 401(k) with 100% company match up to $4,500 and immediate vesting and after‐tax savings Employee Stock Purchase Plan (ESPP) Life and disability insurance Generous holiday, vacation, sick and safety leave Supportive parental, family care, and military leave programs Annual wellness, technology & ergonomic reimbursement programs Social activities including team events and onsites, all‐company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering Catered lunches + snacks & drinks when working in offices #LI-REMOTE At Upstart, your base pay is one part of your total compensation package.

The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location–with our "digital first" philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job‐related skills, experience, and relevant education or training.

Your recruiter can share more about the specific salary range for your preferred location during the hiring process. In addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k). United States | Remote - Anticipated Base Salary Range $220,700—$300,000 USD Upstart is a proud Equal Opportunity Employer.

We are dedicated to ensuring that underrepresented classes receive better access to affordable credit, and are just as committed to embracing diversity and inclusion in our hiring practices. We celebrate all cultures, backgrounds, perspectives, and experiences, and know that we can only become better together. If you require reasonable accommodation in completing an application, interviewing, completing any pre‐employment testing, or otherwise participating in the employee selection process, please email candidate_accommodations@upstart.com https://www.upstart.com/candidate_privacy_policy #J-18808-Ljbffr