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Internship Machine Learning Engineer New Grad Jobs in Algonquin, IL

AppFolio

Sr. Machine Learning Engineer

Chicago, 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 ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · On-site

$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 JobsInternship Machine Learning Engineer New Grad JobsInternship Machine Learning Engineer New Grad Jobs in Algonquin, IL

Internship Machine Learning Engineer New Grad information

See Algonquin, IL salary details

$24.9K

$41.7K

$86.1K

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

As of Aug 8, 2026, the average yearly pay for internship machine learning engineer new grad in Algonquin, IL is $41,660.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,800.00 and $45,000.00 per year, depending on experience, location, and employer.

What types of projects do machine learning engineer interns typically work on?

Machine Learning Engineer interns often work on hands-on projects such as data preprocessing, model development, and conducting experiments to validate algorithms under the guidance of senior engineers. These projects might include building prototypes, optimizing existing machine learning models, or supporting data collection and annotation efforts. Interns are expected to collaborate closely with data scientists, software engineers, and product teams to align their work with real business needs. This experience not only helps interns build technical skills but also provides insight into how machine learning solutions are integrated into larger products or services.

What does an internship machine learning engineer new grad do?

An Internship Machine Learning Engineer New Grad typically works on developing, testing, and optimizing machine learning models under the guidance of senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, model training, and evaluating model performance. They may also collaborate with cross-functional teams to integrate models into production or contribute to research projects. This role provides hands-on experience with real-world data and the opportunity to learn industry-standard tools and practices.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer new grad?

To thrive as an Internship Machine Learning Engineer New Grad, you need a strong grasp of programming (especially Python), machine learning algorithms, data structures, and a relevant degree or coursework in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Strong analytical thinking, problem-solving abilities, and a willingness to learn make you stand out in this position. These skills enable you to contribute effectively to projects, quickly adapt to new challenges, and support innovative solutions in a fast-evolving field.

What is the difference between Internship Machine Learning Engineer New Grad vs Machine Learning Engineer?

AspectInternship Machine Learning Engineer New GradMachine Learning Engineer
Required CredentialsTypically pursuing or recently completed a Bachelor's or Master's in CS, Data Science, or related fieldsBachelor's or higher in CS, Data Science, or related fields; often requires some professional experience
Work EnvironmentTemporary, learning-focused internship, often part-time or summerFull-time professional role in a team, responsible for deploying ML models and projects
Employer & Industry UsageInternships offered by tech companies, startups, and research labs; industry-wideFull-time roles in tech, finance, healthcare, and other sectors utilizing ML

The main difference between an Internship Machine Learning Engineer New Grad and a Machine Learning Engineer is experience level and job responsibilities. Internships are temporary, learning-focused positions for recent graduates or students, while full-time Machine Learning Engineers handle ongoing projects, deployment, and optimization of ML models in a professional setting.

What are popular job titles related to Internship Machine Learning Engineer New Grad jobs in Algonquin, IL? For Internship Machine Learning Engineer New Grad jobs in Algonquin, IL, the most frequently searched job titles are:
What cities near Algonquin, IL are hiring for Internship Machine Learning Engineer New Grad jobs? Cities near Algonquin, IL with the most Internship Machine Learning Engineer New Grad job openings:
Internship Machine Learning Engineer New Grad jobs near you

Sr. Machine Learning Engineer

AppFolio

Chicago, IL

$107K - $147K/yr

Full-time

Re-posted 2 days ago

AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

180th of 242 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. 
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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