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Manager Remote Machine Learning Engineer Jobs (NOW HIRING)

Calendly

Machine Learning Engineer

Hands-on experience implementing ML models using a managed service (for example, Vertex AI or ... Calendly uses the zip code of an employee's remote work location, or the onsite building location ...

Calendly

Machine Learning Engineer

Well, we are looking for a Machine Learning Engineer who will deliver business value by executing ... Hands-on experience implementing ML models using a managed service (for example, Vertex AI or ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Set up and manage the training environment, including GPU instances and required software. Train ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Set up and manage the training environment, including GPU instances and required software. Train ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · Remote

$125K - $165K/yr

Set up and manage the training environment, including GPU instances and required software. Train ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

USAA

AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$103K - $197K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Configure, manage, and set up AI/ML infrastructure components in cloud/on-prem environments for ...

Accelint

Machine Learning Engineer

We are seeking an experienced Machine Learning Engineer / NLP Engineer to develop intelligent document understanding solutions powered by modern natural language processing (NLP) and large language ...

Canals

Machine Learning Engineer

Denver, CO · Remote

Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Canals

Machine Learning Engineer

New York, NY · Remote

Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk ...

Zencastr

Senior Machine Learning Engineer (Remote)

$107K - $146K/yr

They are seeking a Senior Machine Learning Engineer to design and develop machine learning ... The easiest way to record your remote podcast interviews in studio quality Founded in 2014, the ...

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Manager Remote Machine Learning Engineer information

See salary details

$30.5K

$68.6K

$115.5K

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

As of Aug 19, 2026, the average yearly pay for manager remote machine learning engineer in the United States is $68,617.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $74,500.00 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.

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 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.

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.

Can a manager remote machine learning engineer work remotely?

Yes, a manager remote machine learning engineer can work remotely, as many companies offer remote positions for this role. Success in remote work often depends on strong communication skills, familiarity with collaboration tools, and the ability to manage projects independently.
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Manager Remote Machine Learning Engineer jobs near you
Infographic showing various Manager Remote Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $68,617 per year, or $33 per hour.

Machine Learning Engineer

Calendly

Remote

Full-time

Re-posted 29 days ago

Job description

What's in it for you?
Ready to make a serious impact? Millions of people already rely on Calendly, and we're still in the midst of exciting product growth - it's a fantastic time to join us. Everything you'll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you've ever worked with, then we hope you'll consider allowing Calendly to be a part of your professional journey.
About the team & opportunity
What's so great about working on Calendly's Data Science & Machine Learning team?
We make things possible for our customers through innovation in data, analytics and AI.
Why do we need you? Well, we are looking for a Machine Learning Engineer who will deliver business value by executing the full machine learning lifecycle hands-on, from problem discovery through model deployment and monitoring. You will report to the head of Data Science & Machine Learning and will be responsible for building and operating ML-powered features that create magical experiences for our customers.
Our team:
  • Drives business insights, strategic decision making, executive level and cross organizational business growth, and magical customer experiences for our end customers through impactful innovation.
  • Works closely with product, design, marketing, customer success, and engineering teams to implement ML models that improve the customer journey in service to growth and efficiency (for example, understanding the relationships among customers' behavior and business performance).
  • Has a strong product focus and passion for using machine learning to solve real world problems, and understands that being an effective MLE is about collaborating with people as much as it is about writing code.

You will join a high performing AI team and be an integral part of building new, machine learning based experiences for internal and external customers alike.
What you'll do
On a typical day, you'll own features end to end within our ML ecosystem, with growing independence and impact.
  • Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics.
  • Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team.
  • Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly.
  • Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward.
  • Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines.
  • Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team's on-call rotation and incident response.
  • Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies.
  • Be a frequent user of AI Tools and champion of adoption to the rest of the company.

What do we need from you?
  • 4+ years of industry experience in applied Machine Learning or closely related fields (or equivalent combination of education and experience) with a demonstrated track record of shipping and operating ML models in production.
  • Deep and demonstrated ability to traverse the full spectrum of ML life cycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and retraining
  • Experience developing and implementing statistical and ML models to uncover patterns, trends, and predictions in areas such as revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, or natural language processing.
  • Hands-on experience implementing ML models using a managed service (for example, Vertex AI or SageMaker) for high-traffic, low-latency, large-data applications that produced tangible impact for end users.
  • Understanding of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real product use cases.
  • Strong programming (Python / Scala / Java / SQL etc) and data engineering skills
  • Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow and VertexAI
  • Experience working with time series data and related machine learning problems. Working knowledge of semantic search and embeddings
  • Recognize when to seek assistance and willing to learn whatever is needed to get the job done; curiosity and growth mindset are essential.
  • You have strong verbal and written communication skills. Ability to communicate complex technical concepts to both technical and business stakeholders. You are comfortable working remotely and with enabling tools like Slack, Confluence, etc.
  • Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time

#LI-DNI
What's in it for you?
Ready to make a serious impact? Millions of people already rely on Calendly's products, and we're still in the midst of our growth curve - it's a fantastic time to join us. Everything you'll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you've ever worked with, then we hope you'll consider allowing Calendly to be a part of your professional journey.
Our Hiring Process:
We aim to provide an inclusive and equitable candidate experience to everyone who expresses interest in working at Calendly. To learn more about our hiring process, please visit our careers page at www.careers.calendly.com.
Once selected for an opportunity, the recruiter assigned to the role will keep you informed every step of the way. Have questions? Let your recruiter know! Want to share your experience? We are passionately committed to improving and building on our process, and we consider feedback a gift.
If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please contact us at recruiting@calendly.com .
Calendly is registered as an employer in many, but not all, states. If you are located in Alaska, Alabama, Delaware, Hawaii, Idaho, Montana, North Dakota, South Dakota, Nebraska, Iowa, West Virginia, and Rhode Island, you will not be eligible for employment. Note that all individual roles will specify location eligibility.
All candidates can find our Candidate Privacy Statement here
Candidates residing in California may visit our Notice at Collection for California Candidates here: Notice at Collection
Tier 1 Salary Hiring Range
$202,542-$245,434 USD
Tier 2 Salary Hiring Range
$185,664-$224,981 USD
Tier 3 Salary Hiring Range
$168,785-$204,528 USD
The ranges listed above are the expected annual base salary for this role, subject to change.
Calendly takes a number of factors into consideration when determining an employee's starting salary, including relevant experience, relevant skills sets, interview performance, location/metropolitan area, and internal pay equity.
Base salary is just one component of Calendly's total rewards package. All full-time (30 hours/week) employees are also eligible for equity awards, and competitive benefits. Eligible Sales employees also qualify for a Sales Incentive program.
Calendly uses the zip code of an employee's remote work location, or the onsite building location if hybrid, to determine which metropolitan pay range we use. Current geographic zones are as follows:
  • Tier 1: San Francisco, CA, San Jose, CA, New York City, NY
  • Tier 2: Chicago, IL, Austin, TX, Denver, CO, Boston, MA, Washington D.C., Philadelphia, PA, Portland, OR, Seattle, WA, Miami, FL, and all other cities in CA.
  • Tier 3: All other locations not in Tier 1 or Tier 2

If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please let your Recruiter know when first connecting with them. Calendly is registered as an employer in many, but not all, states. If you are located in Alaska, Delaware, Hawaii, Idaho, Iowa, Montana, Nebraska, North Dakota, Rhode Island, South Dakota, and West Virginia, you will not be eligible for employment. Note that all individual roles will specify location eligibility.
All candidates can find our Candidate Privacy Statement here
Candidates residing in California may visit our Notice at Collection for California Candidates here: Notice at Collection
This role may require occasional travel for company events, team collaboration, or offsites.

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