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Machine Learning Engineer Opt Jobs in Minnesota (NOW HIRING)

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Senior Machine Learning Engineer

Saint Paul, MN ยท On-site

$105K - $144K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

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 ...

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 ...

Machine Learning Engineer II

Minneapolis, MN ยท On-site

$102K - $144K/yr

Worker Type Regular Summary The Machine Learning Engineer II will be a member of the Learning and Active Perception (LEAP) group in AV's MacCready Works division and develop a variety of innovative ...

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Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
What are popular job titles related to Machine Learning Engineer Opt jobs in Minnesota? For Machine Learning Engineer Opt jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Machine Learning Engineer Opt jobs? Cities in Minnesota with the most Machine Learning Engineer Opt job openings:
Development Engineer/LEAD MACHINE LEARNING ENGINEER

Development Engineer/LEAD MACHINE LEARNING ENGINEER

UrBench

Minneapolis, MN โ€ข On-site

$65 - $70/hr

Contractor

Posted 8 days ago


Job description

Local candidates only
Must have local project in recent/Local DL copy
Overall 7+ years of exp
Visa - OPT/CPT/H4 EAD/Gc EAD/L2 EAD/USC/GC only
Rate - $65-70/hr W2 + $7 referral, open for higher rate based on their exp.
Client - TARGET
Location - Minneapolis, MN - Hybrid 2 days onsite
Role - Development Engineer/LEAD MACHINE LEARNING ENGINEER
Duration - 6-12 months contract with long term extension
Must Have:
Kaftka
Machine Learning
Machine Learning Development
Python, Pyspark or Scala
SPARK
Nice to Have:
Java
AS A LEAD MACHINE LEARNING ENGINEER
About Us:
Join our global in-house Tech and Data Sciences team
As Lead Machine Learning Engineer, you will join a Data Sciences team responsible for creating personalized recommendations on Target.com and the Target App. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you will conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.
Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
Qualifications:
  • 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
  • MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience
  • 5 plus years' experience in end-to-end Machine Learning application development, including data pipelining, model optimization, deployment, and API design
  • Highly proficient programming in Python and either PySpark or Scala
  • Experience with ML frameworks such as Pytorch, TensorFlow, xgboost, sklearn, and ONNX
  • Experience with one or more cloud ML services such as Vertex AI/Azure ML/Sagemaker
  • Experience using distributed training frameworks like Spark/Ray/TensorFlow Distribute
  • Experience with serving frameworks such as TorchServe/TensorFlow Serving/FastAPI
  • Good understanding of Big Data tech, specifically Kafka, Spark
  • Experience creating and maintaining CI/CD pipelines for automated model deployment and testing
  • Work in partnership with data scientists, software engineers and product managers to understand the business requirements and translate to machine learning solutions at scale
  • Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
  • Self-driven and results oriented; able to meet tight timelines
  • Ability to collaborate effectively across global team
  • Experience in mentoring the junior team members ML skillset and career development
Nice to Have:
  • PhD in Computer Science, Applied Mathematics, Statistics, Physics or related quantitative field
  • Proficiency in Java
  • This position will operate as a Hybrid/Flex for Your Day work arrangement based on ***'s needs. A Hybrid/Flex for Your Day work arrangement means the team member's core role will need to be performed both onsite at the *** HQ location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by ***.
  • Onsite 1 day a week at minimum. Sometimes teams may require up to 3 days and full Core Weeks attendance.

UrBench is an equal opportunity employer and is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, status as a parent, disability, age, veteran status, or other characteristics as defined by federal, state or local laws.


UrBench logo

About UrBench

Sourced by ZipRecruiter

Nurturing Excellence in the USA Since 2000 Hello, fellow explorer! Welcome to UrBench, where American excellence and expertise have been thriving since 2000. Get ready for a journey beyond the ordinary, because we're not your typical recruitment and staffing company. We're more like the architects of achievement, the conductors of compatibility, and the champions of collaboration right here in the States. Our High Skilled Team Players UrBench's adept team forge success by linking talent and opportunities with integrity and innovation. They empower individuals and organizations, propelling our mission forward. Our Expertise & Skills to All Business Because we're not just another company โ€“ we're your backstage pass to success, deeply rooted in the heart of the USA. With us, you're not a client; you're a collaborator, a co-pilot, and a fellow visionary in the quest for greatness on American soil. From tech revolutions to industry shifts, we've been here, shaping the landscape and creating success stories. Let's embark on this journey together, crafting history, one exceptional partnership at a time.

Industry

Recruiting and staffing services

Company size

1 - 10 Employees

Headquarters location

Austin, TX, US