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Manager Remote Machine Learning Engineer Jobs in Hobart, IN

Databricks

Manager, Field Engineering - MFG

Chicago, IL · On-site +1

Louis) While candidates in the listed locations are encouraged for this role, we are open to remote ... machine learning, or AI). * A deep technical understanding of the impact that Data + AI can drive ...

zerohash

Senior Program Manager (Remote)

Chicago, IL · Remote

$118K - $119K/yr

Bachelor's degree in Computer Science, Engineering, Business or a related field * 7+ years of ... Initiative - An ability and passion for learning and asking questions. We will champion you ...

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All JobsMachine Learning Engineer JobsManager Remote Machine Learning Engineer JobsManager Remote Machine Learning Engineer Jobs in Hobart, IN

Manager Remote Machine Learning Engineer information

See Hobart, IN salary details

$30.2K

$67.9K

$114.2K

How much do manager remote machine learning engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for manager remote machine learning engineer in Hobart, IN is $67,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,400.00 and $73,700.00 per year, depending on experience, location, and employer.

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.
Manager Remote Machine Learning Engineer jobs near you

Manager, Field Engineering - MFG

Databricks

Chicago, IL • On-site, Remote

Full-time

Re-posted 8 days ago

Job description

REQ ID - FEQ327R483

Location(s): Central US (Texas, Illinois, St. Louis)

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in the Central United States.

The Databricks Field Engineering team activates and accelerates the value our customers get from their data and AI.  Major Enterprises in the U.S. are leveraging the Databricks Data Intelligence Platform to securely deliver AI's potential to every audience, at scale.  Our Field Engineering team is hiring a dynamic Solutions Architecture leader who is not only focused on team culture but also can translate their team vision into a tangible and effective strategy in order to drive our customers' Data + AI experiences forward.

As a Field Engineering Manager, you will manage a team of Solutions Architects (SAs) for the Manufacturing Segment of Databricks' Field Engineering organization. You will lead a dynamic team of pre-sales professionals focusing on enterprise software, big data/analytics, data engineering, data science, and AI. You will partner with Sales (and other Field Engineering technical segments) to increase revenue and help customers become wildly successful. You'll scale and maintain an outstanding Field Engineering team that is efficient in its operations to help accelerate Databricks' growth in the market.

The impact you will have:

  • You will hire, train, grow, and manage a bar-raising team of Solutions Architects for a company in high-growth mode.
  • Make your customers extremely successful with Databricks and provide outsized value to their businesses.
  • You will maintain a robust hiring pipeline at all times.
  • Establish relationships across the business to make your customers and team successful.
  • Partner with sales leadership to hit sales and consumption targets while ensuring customer success
  • Keep your team of SAs ahead of the technical curve. You will make sure that your team is continuously learning, maintaining advanced knowledge of the data+AI technology stack, and working to provide our customers with the most comprehensive solutions for their needs

What we look for:

  • 3+ years of experience building and leading technical pre-sales teams - hiring, onboarding, coaching, and enabling pre-sales professionals
  • 7+ years of experience in the Data + AI space with a technical product (i.e., data warehousing, big data, data science, machine learning, or AI).
  • A deep technical understanding of the impact that Data + AI can drive within various industry segments
  • Technical competence to earn the trust of Engineering talent and leadership at Databricks.
  • Trusted advisor to technical executives who guide strategic data infrastructure decisions.
  • Lead a team through best practices for technical qualification, proof of concepts, architecture discussions, and product demonstrations.
  • Experience hiring pre-sales professionals, ramping them up to be successful, promoting them into larger roles, identifying and addressing performance issues, and implementing improvement plans. 
  • Create a positive team culture and help foster working relationships between Field Engineering, Sales, and other important internal partners.
  • Experience working with other teams such as Product Management, Engineering, and Customer Success.
  • Demonstrated architectural influence. Able to influence and review complex architectures, guiding your team and customers toward ideal solutions that scale.

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