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Machine Learning Engineer Jobs in South Bend, IN

TouchTronics Inc

Manufacturing Engineer

Elkhart, IN · On-site

$75K - $85K/yr

... learning customarily acquired through specialized education. As the Manufacturing Engineer, you ... Ability to use hands and fingers to operate hand tools/equipment and machinery occasionally.

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in South Bend, IN

Machine Learning Engineer information

See South Bend, IN salary details

$30.9K

$126.4K

$190K

How much do machine learning engineer jobs pay per year?

As of Jul 18, 2026, the average yearly pay for machine learning engineer in South Bend, IN is $126,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,600.00 and $152,200.00 per year, depending on experience, location, and employer.

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-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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 strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What job categories do people searching Machine Learning Engineer jobs in South Bend, IN look for? The top searched job categories for Machine Learning Engineer jobs in South Bend, IN are:
What cities near South Bend, IN are hiring for Machine Learning Engineer jobs? Cities near South Bend, IN with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Postdoctoral Research Fellow

Postdoctoral Research Fellow

University of Notre Dame

Notre Dame, IN • On-site

Full-time

Posted 5 days ago

University Of Notre Dame rating

7.4

Company rating: 7.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

300th of 555 rated colleges and universities

Job description

Description
The University of Notre Dame invites applications for a Postdoctoral Research Fellow with deep expertise in quantitative data analysis, data science, and artificial intelligence (AI). This fellow will join a dynamic, interdisciplinary team working at the intersection of data innovation and sustainability science, aligned with the values and principles of integral ecology.
The research fellow will contribute to a new research project that is creating a Pan-Amazon Evidence and Action Hub for socio-economic and ecological flourishing. The hub will systematically synthesize and harmonize remote sensing, survey, census, and citizen science data to support analyses of issues for action in partnership with local communities and Indigenous Peoples in the Amazon region. Fellows will integrate and harmonize fragmented data from diverse sources into a coherent, usable form to support novel analyses that advance key sustainability goals. The work of the Hub will generate findings to support the design and adoption of interventions that respond to changing needs of the region and its people around climate change, energy, mining, soil and water contamination, food production and livelihoods.
The postdoctoral fellow will join a cohort that functions as a central research skills hub, supporting and elevating the sustainability-related research efforts of faculty and students across Notre Dame. The fellows will help advance impactful, solution-oriented sustainability research that engages ecological, social, economic, and ethical dimensions in an integrated manner.
The postdoctoral fellow will assume the following key responsibilities:
  • Collaborate with faculty to design, implement, and support sustainability-related research projects requiring advanced data analytics.
  • Develop and maintain a centralized platform for the Pan-Amazon Evidence and Action Hub that hosts diverse and harmonized sustainability-related datasets, including environmental, socioeconomic, cultural, and geospatial data.
  • Design and implement reproducible pipelines that ingest, clean, and harmonize fragmented data from remote sensing, survey, census, administrative, and citizen science sources into coherent, analysis-ready datasets with documented lineage and quality metrics.
  • Build tools and interfaces (APIs, catalogs, dashboards, or reproducible workflows) that make Hub data discoverable and usable by faculty, students, and partner organizations with varying technical capacity.
  • Explore applications of AI methods, including large language models and natural language processing, for extracting structured information from unstructured sources(e.g. reports, policy documents, gray literature, or citizen science observations),
  • Apply advanced statistical, machine learning, and AI techniques to analyze complex datasets and uncover actionable insights.
  • Co-author and support high-impact, interdisciplinary research publications in leading sustainability and environmental science journals.
  • Engage in collaborative grant writing and proposal development to sustain and expand the cohort's research initiatives.

This search is conducted with leadership from Notre Dame's Just Transformations to Sustainability Initiative and Data, AI, and Computing Initiative, both significant investments from the Provost's Office. The Just Transformations to Sustainability Initiative is Notre Dame's University-wide effort to build a sustainable future where people and nature flourish together. The Data, AI, and Computing Initiative's core aim is to advance purposeful data, AI, and computing - excelling in foundational research while catalyzing interdisciplinary collaboration and real-world translation to address pressing societal challenges.
This is a full-time position available with an initial appointment of one-year, renewable for an additional year on the basis of satisfactory performance and availability of funding.
Qualifications
Required Qualifcations:
  • Ph.D. (in hand by the starting date) in Data Science, Computer Science, Statistics, Geography, Environmental Science, or a related field with a strong computational focus. Applicants with interdisciplinary degrees are welcome.
  • Strong data engineering skills in Python and/or R, preferably in building reusable data pipelines rather than one-off analysis scripts.
  • Demonstrated experience harmonizing heterogeneous data sources: reconciling inconsistent schemas, units, geographies, and vintages across datasets such as remote sensing products, surveys, censuses, and administrative records, and documenting those decisions in a reproducible way.
  • Expertise in geospatial data, including working across raster and vector formats, coordinate reference systems, and spatial aggregation or interpolation across mismatched administrative and ecological units.
  • An interest or experience in using machine learning or AI tools with environmental or socioeconomic data
  • Excellent communication skills and the ability to translate technical infrastructure decisions for collaborators from a wide range of disciplines.

Application Instructions
Interested candidates must submit a CV, cover letter, and a recent publication or dissertation chapter. Candidates should be prepared to share references upon request.

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