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Machine Learning Engineer New Grad Jobs in Milwaukee, WI

Our engineering team leverages emerging technologies and best practices across data security ... Work with clients to design, develop, and deploy new architectures to support machine learning ...

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$103K - $141K/yr

Our engineering team leverages emerging technologies and best practices across data security ... Work with clients to design, develop, and deploy new architectures to support machine learning ...

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$102K - $141K/yr

Deloitte's Strategy & Transactions team is seeking a Senior AI Engineer to join SFL Scientific, a ... new architectures to support machine learning & automation applications • Leverage advanced ...

... grad in a Data Science / Machine Learning position. * Professional experience with Python ... Proven leadership abilities in an engineering environment in driving operational excellence and ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Senior AI Engineer

Racine, WI

$98K - $134K/yr

This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI ...

Lead ML Ops Engineer

Milwaukee, WI · On-site

$101K - $133K/yr

This role manages a team of Machine Learning Operations Engineers, oversees the end-to-end machine-learning strategy and execution, sets vision for MLOps, and ensures alignment with business goals.

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Machine Learning Engineer New Grad information

See Milwaukee, WI salary details

$31K

$126.9K

$190.6K

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

As of Jun 26, 2026, the average yearly pay for machine learning engineer new grad in Milwaukee, WI is $126,869.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $152,700.00 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 are the most commonly searched types of Machine Learning Engineer New Grad jobs in Milwaukee, WI? The most popular types of Machine Learning Engineer New Grad jobs in Milwaukee, WI are:
What are popular job titles related to Machine Learning Engineer New Grad jobs in Milwaukee, WI? For Machine Learning Engineer New Grad jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer New Grad jobs in Milwaukee, WI look for? The top searched job categories for Machine Learning Engineer New Grad jobs in Milwaukee, WI are:
Infographic showing various Machine Learning Engineer New Grad job openings in Milwaukee, WI as of June 2026, with employment types broken down into 9% As Needed, 55% Full Time, and 36% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $126,869 per year, or $61 per hour.

AI Engineer/ML Engineer - Senior Developers - AI Training - Milwaukee, US

Prolific Academic Ltd

Milwaukee, WI • On-site, Remote

$80/hr

Full-time

Posted 8 days ago


Job description

AI & Machine Learning Engineer - AI TrainingAbout Prolific

Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world.

Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.

The role

We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models.

Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.

What you'll bring
  • Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
  • Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment.
  • Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
  • LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows.
  • Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
  • Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content.
What you'll be doing in the role
  • Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
  • Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness.
  • Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness.
  • Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down.
  • Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics.
Key Technologies
  • Frameworks: expert proficiency in PyTorch or TensorFlow/Keras.
  • Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers.
  • Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain.
  • Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation.
Why Prolific is a great platform to join as a Participant

Joining our Expert Network will give you the chance to influence the AI models of the future using your professional expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.

We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity.
Click here to apply directly - https://app.prolific.com/register/participant/waitlist/?campaign_code=C14EMWJI
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Privacy Statement

By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.