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Manager Remote Machine Learning Engineer Jobs in Illinois

Senior ML Engineer

Chicago, IL ยท Remote

$180K - $240K/yr

... Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary ... Collaborating with various teams and product managers to develop and implement ML based solutions ...

Senior Machine Learning Test Engineer

Ohio, IL ยท On-site +1

$104K - $135K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... You will report to an Engineering Manager in Research Enablement. Location: United States, East ...

Senior AI/ML Engineer

Springfield, IL ยท Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning ... Collaboration with product managers, architects, and cross-functional teams will ensure solutions ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Manager Remote Machine Learning Engineer information

What is a Manager Remote Machine Learning Engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

What is the difference between Manager Remote Machine Learning Engineer vs Data Scientist?

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

What are the key skills and qualifications needed to thrive as a Manager Remote Machine Learning Engineer, and why are they important?

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

How does a Manager Remote Machine Learning Engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.
What are the most commonly searched types of Remote Machine Learning Engineer jobs in Illinois? The most popular types of Remote Machine Learning Engineer jobs in Illinois are:
What job categories do people searching Manager Remote Machine Learning Engineer jobs in Illinois look for? The top searched job categories for Manager Remote Machine Learning Engineer jobs in Illinois are:
What cities in Illinois are hiring for Manager Remote Machine Learning Engineer jobs? Cities in Illinois with the most Manager Remote Machine Learning Engineer job openings:

Senior ML Engineer

Career Renew

Chicago, IL โ€ข Remote

$180K - $240K/yr

Full-time

Medical, PTO

Posted 6 days ago


Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 180-240K USD plus benefits plus equity.
Since 2017, weโ€™ve been on a mission to use AI to resolve as many conversations as possible while elevating human agents to do what they are uniquely good at.

We are looking for a Senior Machine Learning Engineer with 5+ years of experience to join our small but mighty ML team building production-grade AI voice agents used by enterprise customers like AAA and Fanatics. You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ship LLM-powered systems that handle real, high-stakes conversations at scale โ€” not just run experiments.


What will you be doing?

  • Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields

  • Translating the latest research into high-performing systems and models that can be practically applied to enhance user experiences

  • Help set the team's strategic direction, cultivating an environment that encourages innovation and professional growth

  • Actively engaging in all aspects of development, from ideation and experimentation to implementation and deployment

  • Collaborating with various teams and product managers to develop and implement ML based solutions, ensuring performance optimization and alignment with broader business goals

Requirements:
5 - 10 years of experience in applied ML engineering, building production systems in Python with LLMs or NLP (Mandatory)
Experience building production systems in Python (Mandatory)
Familiarity with low-latency production ML systems (Mandatory)
Experience working at a high-growth startup (Mandatory)
Background in NLU, NLP, or conversational AI (Nice-to-have)
BS/MS/PhD in CS, ML, Mathematics, or closely related field with ML coursework (Mandatory)
Why you should join
  • Industry leader in Voice AI for customer service since 2017 โ€” powering enterprise customers like AAA and Fanatics where 50%+ of callers get fully resolved by the bot with higher satisfaction scores than human agents.
  • $113M raised from top-tier investors including Stripes, Salesforce Ventures and Norwest โ€” Series B closed in 2022 at $78M with strong backing from day one.
  • Work on genuinely cutting-edge AI problems โ€” low latency inference, hallucination reduction, prompt injection guardrails and dynamic conversation design at the frontier of what's possible with LLMs today.
  • Small team means real ownership and real impact โ€” every improvement you ship moves the needle for enterprise customers in high-stakes scenarios (think: someone stranded on the road calling AAA).
  • Remote-first with strong perks โ€” flexible vacation, paid sabbatical after 5 years, comprehensive health benefits, wellness stipend and a tech/learning stipend for conferences, books and courses. Competitive salary ($180Kโ€“$230K) plus meaningful equity.