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Machine Learning Engineer Opt Jobs in Minnesota (NOW HIRING)

NxT Level

Principal AI / ML Engineer

Minneapolis, MN · On-site

We're looking for a Principal Machine Learning Engineer to build AI features for the family. Qualifications: * A confident craftsperson who possesses problem-solving tools and can discuss multiple ...

Deloitte

AI Solutions Architect

Minneapolis, MN · On-site

$65.75 - $86.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

Senior AI Engineer - SFL Scientific

Minneapolis, MN · On-site

$109K - $149K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

THOMSON REUTERS

Lead Research Engineer

Eagan, MN · On-site +1

$104K - $137K/yr

Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ... Unless you opt-out, our AI system will assess the information provided by you and compare it to the ...

VivaQuant, Inc.

AI Engineer

Saint Paul, MN · On-site

$110K - $130K/yr

Rhythm Express is seeking an AI Engineer to join our team to develop and implement machine learning algorithms used in cardiac remote monitoring. This position will work alongside and collaborate ...

Thomson Reuters

Lead Research Engineer

Eagan, MN · On-site

$104K - $137K/yr

Experience integrating Machine Learning solutions into production-grade software with a sound ... Unless you opt-out, our AI system will assess the information provided by you and compare it to the ...

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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.

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 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 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 job categories do people searching Machine Learning Engineer Opt jobs in Minnesota look for? The top searched job categories for Machine Learning Engineer Opt jobs in Minnesota 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:
Machine Learning Engineer Opt jobs near you
Principal AI / ML Engineer

Principal AI / ML Engineer

NxT Level

Minneapolis, MN • On-site

Full-time

Medical, Retirement, PTO

Posted 17 days ago

Job description

Our client is a digital consumer product. They're building social features using LLMs and Machine Learning to add to user experience. We're looking for a Principal Machine Learning Engineer to build AI features for the family.
Qualifications:
  • A confident craftsperson who possesses problem-solving tools and can discuss multiple approaches while preferring the best approach given the constraints.
  • A scientific artist and artistic scientist who can navigate complexity and bring clarity to intricate problems while appreciating simplicity as the highest sophistication.
  • A pragmatic optimizer who identifies the need for change, articulates it, and drives incremental improvements toward ambitious goals.
  • An advocate for team collaboration and open communication.
  • Possesses comprehensive knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and advanced NLP techniques.
  • Significant experience in AI/ML engineering with a strong data science background.
  • Demonstrated ability in designing and training LLMs.
  • Expertise in Databricks/Apache Spark for large-scale data processing in AI/ML applications.
  • Proficiency with AWS Bedrock and Comprehend.
  • Demonstrated leadership in AI/ML solutions in a commercial environment.
  • Proficiency in programming languages such as R, Python, and Java, with a focus on data exploration and processing.
  • Proven ability to lead and inspire teams of senior engineers and data scientists.
  • Effective individual contributor within a collaborative team environment.
  • Strong analytical, problem-solving, and communication skills.

Responsibilities:
  • Collaborate with the Data team to transform Data Lakehouse potential into actionable insights and services that enhance user experiences.
  • Shape AI/ML strategies, particularly in LLMs, to drive business outcomes and establish data science principles.
  • Implement technologies in AWS and Databricks for handling and processing large datasets for advanced language model training.
  • Lead data science practices, including model selection and training methodology.
  • Build, train, manage, and host LLMs using Data Lakehouse data.
  • Optimize AI system performance through testing and tuning, leveraging data science and Databricks methodologies.
  • Ensure ethical standards and data privacy compliance in AI solutions.
  • Provide specialized AI/ML expertise to guide the development and optimization of AI features.
  • Stay updated on the latest AI/ML and data science trends, especially in LLMs and AWS, Databricks/Apache Spark technology.

Benefits:
  • Full Medical Coverage: OFW covers 100% of premiums for employees and their families.
  • 401k: Up to a 4% match with immediate vesting.
  • 12 weeks of paid leave for all new parents.
  • Learning & Development stipend for employees.
  • Supportive and flexible working environment, allowing remote work from anywhere.

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