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Founding Machine Learning Engineer Jobs in Minnesota

Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... Required Qualification:- - 5+ years software engineering with 2+ years shipping ML models to ...

Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... Required Qualification:- - 5 years software engineering with 2 years shipping ML models to ...

Impact As a Staff Machine Learning Engineer on Shipt's Personalization Platform team you will drive key AI initiatives. In this role, you'll collaborate with Data Scientists to design and deploy ...

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Founding Machine Learning Engineer information

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

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.
What are popular job titles related to Founding Machine Learning Engineer jobs in Minnesota? For Founding Machine Learning Engineer jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Founding Machine Learning Engineer jobs? Cities in Minnesota with the most Founding Machine Learning Engineer job openings:
Machine Learning Engineer

Machine Learning Engineer

Virtusa

Minneapolis, MN • On-site

Other

Posted 17 days ago


Job description

Role Summary:-


Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.


Ker Responsibilities

- Translate data science prototypes into production-grade ML services and pipelines.

- Build training and inference code with reproducibility, versioning, and automated testing.

- Implement scalable model serving (online/offline), batching, and latency/throughput optimization.

- Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).

- Collaborate with Data Engineering on feature pipelines and data contracts.

- Own production health: drift detection, performance regression, rollback strategies, and incident response.


Required Qualification:-

- 5+ years software engineering with 2+ years shipping ML models to production.

- Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).

- Experience with containers and orchestration (Docker/Kubernetes) and API development.

- Understanding of ML system design (data leakage, training-serving skew, drift).

- CI/CD and DevOps practices applied to ML workloads (MLOps).


Nice to have:-

- Experience with feature stores, model registries, and model monitoring stacks.

- GPU optimization and distributed training experience.

- Experience with responsible AI toolkits and compliance requirements.


 

Role Summary:-


Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.


Ker Responsibilities

- Translate data science prototypes into production-grade ML services and pipelines.

- Build training and inference code with reproducibility, versioning, and automated testing.

- Implement scalable model serving (online/offline), batching, and latency/throughput optimization.

- Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).

- Collaborate with Data Engineering on feature pipelines and data contracts.

- Own production health: drift detection, performance regression, rollback strategies, and incident response.


Required Qualification:-

- 5+ years software engineering with 2+ years shipping ML models to production.

- Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).

- Experience with containers and orchestration (Docker/Kubernetes) and API development.

- Understanding of ML system design (data leakage, training-serving skew, drift).

- CI/CD and DevOps practices applied to ML workloads (MLOps).


Nice to have:-

- Experience with feature stores, model registries, and model monitoring stacks.

- GPU optimization and distributed training experience.

- Experience with responsible AI toolkits and compliance requirements.


 


Virtusa logo

About Virtusa

Sourced by ZipRecruiter

We are builders, makers, and doers with the technical skills and domain expertise to transform your business at scale and speed without disruption. Our unique Engineering First approach blends deep industry expertise and empowered, agile teams, to create holistic solutions that seamlessly move the business forward. We help clients engage with new technology paradigms to creatively build solutions that drive them to the forefront of their industries.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Westborough, MA, US

Year founded

1996

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