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Machine Learning Jobs in Valparaiso, IN (NOW HIRING)

Verstela

Production 1st shift

Crown Point, IN

$16/hr

As a Production Operator, you'll be cross-trained across multiple departments--including packaging, duct, and machine operation--helping the team meet daily production goals while learning new skills ...

Varsity Tutors

Statics Tutor

Valparaiso, IN · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... machines, centroids, moments of inertia, friction, and distributed forces. Ability to explain ...

Diocese of Gary

High School Math Teacher

Merrillville, IN · On-site

$47K - $63K/yr

Designs learning activities to demonstrate the application of mathematics to everyday existence and ... Equipment Uses standard office equipment such as personal computers, printer, copy and fax machines ...

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All JobsMachine Learning JobsMachine Learning Jobs in Valparaiso, IN

Machine Learning information

See Valparaiso, IN salary details

$25.5K

$42.5K

$87.9K

How much do machine learning jobs pay per year?

As of Jun 15, 2026, the average yearly pay for machine learning in Valparaiso, IN is $42,530.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $45,900.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data analysis, and programming. These roles usually involve leadership responsibilities, strategic planning, and may require extensive experience and specialized certifications, with compensation reflecting the seniority and impact of the role.

What is a Machine Learning job?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

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 at large tech companies can earn salaries of $500,000 or more, especially when including bonuses and stock options. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of impactful projects.

What are some typical day-to-day responsibilities in a Machine Learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These jobs typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

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

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

Which 3 jobs will survive AI?

Machine learning engineers, data scientists, and AI ethics specialists are likely to continue thriving as AI advances, due to their expertise in developing, managing, and overseeing AI systems. These roles require specialized skills, critical thinking, and understanding of complex algorithms that are difficult to fully automate. Continuous learning and certification in relevant tools like Python, TensorFlow, or ethical frameworks will support job security in these fields.
What are popular job titles related to Machine Learning jobs in Valparaiso, IN? For Machine Learning jobs in Valparaiso, IN, the most frequently searched job titles are:
What cities near Valparaiso, IN are hiring for Machine Learning jobs? Cities near Valparaiso, IN with the most Machine Learning job openings:
Machine Learning jobs near you

Director, Data Engineering

DwyerOmega

Michigan City, IN • On-site

Full-time

Posted 16 days ago

Job description

Description:

We are seeking a visionary Director, Data Engineering to architect the "data set of the future." This role is not just about reporting; it is about building the scalable, AI-ready infrastructure that will fuel our next generation of manufacturing innovation. You will move the organization beyond traditional data warehousing to a robust Data Lakehouse architecture, ensuring our enterprise data—from shop floor to point-of-sale—is clean, real-time, and ready for advanced GenAI and predictive modeling.

The ideal candidate is a technologist who fluently bridges the gap between the plant floor and the front office. You will be responsible for integrating complex operational data with high-velocity sales and commercial data to create a unified ecosystem. By connecting factory efficiency directly to customer demand and market trends, you will enable us to pivot from reactive operations to a truly predictive enterprise.


Key Responsibilities:

  • Architecting the Future: Define and execute a data infrastructure roadmap centered on a Lakehouse architecture that integrates structured and unstructured data, enabling both real-time operational analytics and high-scale AI/ML workloads.
  • AI-Ready Foundation: Establish the data governance, cataloging, and lineage frameworks necessary to power secure, trusted AI models and Large Language Models (LLMs) across the enterprise.
  • Manufacturing Integration: Partner with OT and Engineering teams to ingest and operationalize IIoT and supply chain data, creating a unified data ecosystem that drives predictive maintenance and factory floor efficiency.
  • Modern Data Stack Leadership: Oversee the transition from legacy BI tools to modern, self-service analytics platforms, ensuring the organization has the agility to derive insights from the data lakehouse.
  • Data Ops & Governance: Lead the transition to MLOps and DataOps methodologies, ensuring data quality, security, and compliance in an increasingly automated environment.
  • Strategic Partnership: Collaborate with business unit leaders to identify and prioritize data products that drive measurable top-line growth or operational cost reductions.
  • Team Leadership: Build and mentor a high-performing team of data engineers, ML engineers, and data architects who are comfortable in both cloud-native environments and complex legacy manufacturing systems.






Requirements:

Qualifications and Technical Requirements:

  • Strategic Experience: 15+ years in data strategy, architecture, and engineering, with at least 5 years in a leadership role driving organizational change.
  • 5+ years in a leadership role managing data & analytics teams.
  • Architecture Expertise: Demonstrated experience designing and deploying Lakehouse architectures (e.g., Databricks, Snowflake, or similar) at scale.
  • AI/ML Fluency: Proven experience operationalizing AI/ML models within an enterprise environment; deep understanding of data preparation for LLMs and generative AI.
  • Cloud Proficiency: Extensive experience with Azure (or equivalent cloud hyperscaler) data stacks (e.g., Synapse/Fabric, ADLS Gen2, Azure AI).
  • Tooling: Advanced proficiency in Python, Spark, and SQL; strong experience with CI/CD for data pipelines and infrastructure-as-code.
  • Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.
  • Soft Skills: A "product manager" mindset for data; the ability to translate complex technical architectural debt into business-friendly value proposition


Essential/Preferred Skills:

  • Experience with data governance frameworks and tools.
  • Exposure to advanced analytics, data science, or machine learning initiatives.
  • Experience in manufacturing, industrial, or eCommerce environments preferred.


Work Conditions and Physical Requirements:

  • Ability to work in both office and manufacturing environments.
  • Availability to work outside of core business hours, including nights, weekends, and holidays when required for system upgrades or migrations.
  • Required to sit or stand for long periods of time.
  • The ability to lift 30-50 lbs without assistance.
  • Local and/or international travel will be required as needed (10-15%) including some extended stays on location for education or deployments. Must have a valid driver's license and Passport.