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Machine Learning Engineer New Grad Jobs in Pinckney, MI

Sr. Data Engineer

Ann Arbor, MI · On-site

$103K - $140K/yr

The role involves working across various data domains and collaborating with machine learning engineers to enhance production processes. Responsibilities : • Work across domains--for example, all ...

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100K - $132K/yr

Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ... New York City, San Francisco, Los Angeles, and/or Irvine, CA; McLean, VA; Washington, DC. The base ...

Lead Perception Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

A system thinker with technical depth in machine learning approaches to complex systems. This ... Incorporate data-driven approaches to improve system performance and unlock new capabilities for ...

Lead Perception Engineer

Ann Arbor, MI

$100K - $132K/yr

A system thinker with technical depth in machine learning approaches to complex systems. This ... Incorporate data-driven approaches to improve system performance and unlock new capabilities for ...

Lead Perception Engineer

Ann Arbor, MI

$100K - $132K/yr

A system thinker with technical depth in machine learning approaches to complex systems. This ... Incorporate data-driven approaches to improve system performance and unlock new capabilities for ...

Lead Perception Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

A system thinker with technical depth in machine learning approaches to complex systems. This ... Incorporate data-driven approaches to improve system performance and unlock new capabilities for ...

Senior Research Engineer

Ann Arbor, MI · Hybrid

$102K - $140K/yr

Experience integrating Machine Learning and Generative AI solutions into production-grade ... New York City, San Francisco, Los Angeles, and/or Irvine, CA; McLean, VA; Washington, DC. The base ...

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Machine Learning Engineer New Grad information

See Pinckney, MI salary details

$29.7K

$121.4K

$182.4K

How much do machine learning engineer new grad jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning engineer new grad in Pinckney, MI is $121,390.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,700.00 and $146,100.00 per year, depending on experience, location, and employer.

What is a Machine Learning Engineer New Grad job?

A Machine Learning Engineer New Grad job is an entry-level role for recent graduates specializing in machine learning and artificial intelligence. It typically involves developing, training, and deploying machine learning models, working with large datasets, and optimizing algorithms for performance. New grads in this role often collaborate with data scientists, software engineers, and product teams to integrate models into applications. Employers look for proficiency in programming (Python, TensorFlow, PyTorch), a strong foundation in ML concepts, and experience with data processing. This role provides an opportunity to gain hands-on industry experience and grow technical skills in real-world applications.

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

To thrive as a Machine Learning Engineer New Grad, a strong background in computer science, statistics, and mathematics, often supported by a relevant degree, is essential. Familiarity with programming languages like Python or Java, machine learning frameworks (such as TensorFlow or PyTorch), and basic knowledge of data tools and cloud platforms is typically required. Effective problem-solving, eagerness to learn, and clear communication help new grads excel when collaborating on projects and learning from senior team members. These skills and qualities are vital for adapting quickly, contributing to team goals, and building a successful foundation in this fast-evolving technical field.

What are the typical day-to-day tasks of a Machine Learning Engineer New Grad?

As a Machine Learning Engineer New Grad, your daily tasks often include collecting and preprocessing data, developing and testing machine learning models, and analyzing model performance. You may work closely with data scientists and software engineers to integrate models into production systems and address real-world business problems. Participating in team meetings, code reviews, and collaborative projects is common, providing opportunities to learn best practices and receive mentorship. This hands-on, varied workload helps you quickly build technical and collaborative skills early in your career.

What cities near Pinckney, MI are hiring for Machine Learning Engineer New Grad jobs? Cities near Pinckney, MI with the most Machine Learning Engineer New Grad job openings:
Data Scientist -- Machine Learning Practitioner

Data Scientist -- Machine Learning Practitioner

BlueConduit

Ann Arbor, MI • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

Company overview

BlueConduit is an infrastructure analytics SaaS company and social enterprise helping communities make better, faster, and more equitable decisions about critical water infrastructure. Our founding team pioneered predictive modeling for lead service line replacement in Flint, Michigan, and BlueConduit now works with hundreds of cities and utilities across North America.

Our platform helps utilities, municipalities, government agencies, and consultants combine fragmented infrastructure records, field observations, geospatial data, and predictive models to identify risk, prioritize work, meet compliance requirements, and communicate clearly with the public. We are a remote-first team committed to using data science for social good and building tools that are trusted by the people making high-stakes infrastructure decisions.

The role

BlueConduit is hiring a Data Scientist to improve and expand the machine learning models at the core of our infrastructure analytics platform. In this role, you will work on models that help cities prioritize infrastructure investments, reduce risk, and improve drinking water outcomes. You will strengthen our existing modeling workflows, help launch new model products and asset classes, and communicate results clearly to both technical and nontechnical audiences.

This is a strong fit for someone who combines rigorous applied ML judgment with product-minded execution: you enjoy messy real-world data, care about model validation and uncertainty, can build repeatable workflows rather than one-off analyses, and like explaining technical work to people who need to act on it.

In this role you will be expected to be using the latest available AI tools to code productively. You will need to understand what you’re building and coding, and understand agentic AI workflows that involve best practices, including unit tests, built-in code reviews, and extensive documentation in your commits for fellow data scientists and software engineers.

This role reports to the VP of Data Science.

What you’ll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduit’s infrastructure analytics products
  • Help design, build, and launch new model products and model classes that broaden the assets and risks BlueConduit can predict
  • Improve data science workflows, model evaluation, reproducibility, and handoffs into software/product systems
  • Work with heterogeneous municipal, infrastructure, geospatial, and field-observation datasets to generate actionable risk predictions
  • Design validation approaches and communicate model uncertainty, limitations, and tradeoffs clearly to internal teams and customers
  • Use modern AI coding tools such as Claude Code, Codex, or similar systems to accelerate development while applying strong independent programming judgment
  • Use multiple AI agents to contribute to extremely robust workflows and code pipelines with built-in testing and reviews
  • Support customer-facing analysis and present findings in ways that are clear, accurate, and useful for nontechnical decision-makers
  • Contribute to R&D that scales the impact, reliability, and reach of BlueConduit’s predictive methods

BlueConduit is a small, remote, and growing team, so this is an opportunity to shape both the role and the next generation of our data science products.

What we’re looking for
  • Strong Python-based data science experience, including pandas, NumPy, scikit-learn, and production-quality analysis workflows
  • An undergraduate degree in a quantitative field (e.g., CS, math, stats, physics)
  • Experience building, validating, and improving machine learning or statistical models on messy real-world data
  • Experience building repeatable data science workflows in a product at a SaaS company or similarly operational environment
  • Ability to communicate modeling results, uncertainty, and tradeoffs clearly to technical and nontechnical stakeholders
  • Fluency using modern AI coding tools – including coordinating work of AI agents – to accelerate development, grounded in strong independent programming ability and judgment
  • Strong data visualization, verbal communication, and written communication skills
  • Comfort with Git-based development workflows
  • Attention to detail, curiosity, and commitment to building models that are understandable, usable, and trusted by the people making infrastructure decisions
  • Passion for socially impactful data science, environmental justice, and public-interest technology
We’re especially interested in candidates with one or more of the following
  • A rigorous graduate degree in a quantitative field, or equivalent applied experience
  • Experience modeling asset classes beyond BlueConduit’s current water distribution portfolio, such as fire risk, wastewater, hydraulic systems, climate risk, insurance risk, or other infrastructure domains
  • Experience with geospatial data, GIS systems, GeoPandas, or spatial modeling
  • Experience creating a new model product or extending an existing model product to a new domain or asset class
  • Experience with both global/cross-location models and local/site-specific models
  • Experience with methodologies beyond classical ML, such as neural networks, transformers, transfer learning, or other modern ML approaches
  • Experience with cloud-based model workflows, model tracking, versioning, Databricks, PySpark, or distributed computing
  • Familiarity with infrastructure, water quality, government data, or regulated public-sector decision environments
  • Experience working in Agile product development environments
  • Aptitude and interest in building with rapid iteration cycles involving prototyping, receiving feedback, and rebuilding
Location

Remote

Compensation
  • Expected salary range: $140,000–$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching