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Machine Learning Engineer New Grad Jobs in Illinois

AppFolio

IL

$107K - $147K/yr

It enables a new generation of intelligent capabilities across our products, including Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

AppFolio

Staff Machine Learning Engineer - Leasing

Chicago, IL · On-site

$17.50 - $20.50/hr

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and ... Partner with Voice & Agents and Research ML to evaluate new capabilities -- fine-tuning approaches ...

AppFolio

IL

$17.50 - $20.50/hr

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and ... Partner with Voice & Agents and Research ML to evaluate new capabilities -- fine-tuning approaches ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL

$126K - $166K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off‑sites * Equipment and learning budget to help you do your best work and keep up with ...

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All JobsMachine Learning Engineer New Grad JobsMachine Learning Engineer New Grad Jobs in Illinois

Machine Learning Engineer New Grad information

See Illinois salary details

$30.5K

$124.8K

$187.5K

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

As of Aug 23, 2026, the average yearly pay for machine learning engineer new grad in Illinois is $124,780.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,400.00 and $150,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer new grad?

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 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 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 most commonly searched types of Machine Learning Engineer New Grad jobs in Illinois?

The most popular types of Machine Learning Engineer New Grad jobs in Illinois are:

What are popular job titles related to Machine Learning Engineer New Grad jobs in Illinois?

For Machine Learning Engineer New Grad jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer New Grad jobs in Illinois look for?

The top searched job categories for Machine Learning Engineer New Grad jobs in Illinois are:

What cities in Illinois are hiring for Machine Learning Engineer New Grad jobs?

Cities in Illinois with the most Machine Learning Engineer New Grad job openings:

Machine Learning Engineer New Grad jobs near you
Infographic showing various Machine Learning Engineer New Grad job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $124,780 per year, or $60 per hour.

Sr. Machine Learning Engineer

AppFolio

IL

$107K - $147K/yr

Full-time

Re-posted 17 days ago

AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

184th of 246 rated software companies

Job description

Hi, We're AppFolio
We're innovators, changemakers, and collaborators. We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do business. We're transforming Property Management; how property managers operate, how residents live, and how intelligence flows across an entire industry.
Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products, and a core layer delivering intelligent, high-impact experiences directly to our customers.
At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives—such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making.
Who We Are Looking For
We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio's production voice and chat agent pipelines, working at the intersection of LLM agent frameworks, real-time voice technology, and streaming infrastructure.
You will work with Product, Voice channel, and ML Platform teams to translate cutting-edge agent and voice research into reliable, low-latency, multi-channel experiences that scale across our entire customer base.
Your Impact
  • Ship Voice & Text Agents: Architect and ship voice and text agent pipelines that handle real-time, multi-turn customer interactions.
  • Reasoning vs. Latency: Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.
  • Lead a Pod: Lead a small pod of ML and platform engineers; raise the bar on agent evaluation, observability, and incident response.
  • Define Quality: Partner with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality.
  • Optimize for Voice: Drive selective Small Language Model (SLM) fine-tuning and inference optimization for voice latency and cost.
Qualifications
  • You have shipped production AI agents serving real users in voice and/or text channels.
  • You think in pipelines and systems, not just models.
  • You move fast, deliver impact, and maintain sound engineering judgment.
  • You are humble, collaborative, and low-ego, and you elevate those around you.
  • You value work-life balance as a foundation for sustained high performance.
Must Have
  • Agent frameworks: Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).
  • Voice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands the trade-offs between end-to-end voice models and modular STT → LLM → TTS architectures.
  • LLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.
  • Telephony & cloud: Production experience with Twilio (or comparable telephony) and AWS.
  • Engineering: Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.
  • ML fundamentals: Solid foundation in deep learning, model evaluation, and inference optimization; able to deploy with Docker on AWS.
  • Leadership: Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.
Nice to Have
  • Experience fine-tuning Small Language Models for domain-specific voice applications.
  • Familiarity with RAG over structured business data and tool-using agents over API surfaces.
  • Prior experience in regulated or customer-facing industries with strict reliability requirements.
  • Publicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.
Location
Find out more about our locations by visiting our site. 
All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.
Compensation & Benefits
The compensation that we reasonably expect to pay for this role is: 167,200 - 209,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.
Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits - see here.

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