2

Remote Machine Learning Engineer Jobs in North Hollywood, CA

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting meaningful signals from multimodal time-series data. This role focuses on building robust, real-time ...

next page

Showing results 1-20

Remote Machine Learning Engineer information

See North Hollywood, CA salary details

$33.2K

$135.7K

$203.8K

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

As of Sep 3, 2026, the average yearly pay for remote machine learning engineer in North Hollywood, CA is $135,655.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,900.00 and $163,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning engineer?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

What are the key skills and qualifications needed to thrive as a remote machine learning engineer?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What are some typical challenges faced by remote machine learning engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

Are remote machine learning engineers still in demand?

Remote machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. Skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch are highly sought after, and many companies continue to hire for remote roles in this field.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for this role. The position typically involves tasks such as data analysis, model development, and collaboration through online tools, making remote work feasible with strong communication skills and proficiency in programming languages like Python or frameworks like TensorFlow. However, some roles may require occasional on-site meetings or access to specialized hardware.

What cities near North Hollywood, CA are hiring for Remote Machine Learning Engineer jobs?

Cities near North Hollywood, CA with the most Remote Machine Learning Engineer job openings:

Infographic showing various Remote Machine Learning Engineer job openings in North Hollywood, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $135,655 per year, or $65.2 per hour.

Machine Learning Engineer

Liquid XR

Los Angeles, CA โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, PTO

Posted 5 days ago


Job description

About Us

LiquidXR is an expanding, well-funded startup building a platform to digitize human movement. We are creating next-gen wearables using proprietary MetalGel sensor technology, capturing and feeding movement data to our machine learning-enhanced algorithms and SDKs, which connect to any modern computer or development environment. We are partnered with several high-quality companies co-developing products using our tech, and we are advancing our platform to enable all types of body movement data capture and analysis across multiple areas of use (gaming, sports, performance, XR, and more).

Our tight knit hardware and software team is comprised of experts in product and UX development, biomechanics, algorithms and machine learning, software platform and experience development, electronic engineering, and soft goods industrial design. Individually and collectively, this is a team who gets things done and among us, countless products have been launched worldwide. We are passionate about creating a transformative platform and we are fortunate to work on cool products using our tech along the way.

The Role

We are seeking a Machine Learning Engineer to develop advanced models for extracting meaningful signals from multimodal time-series data. This role focuses on building robust, real-time algorithms that operate on noisy, high-frequency sensor inputs.

You will work on problems involving temporal modeling, representation learning, and inference under real-world constraints.


What You'll Do

  • Design and implement machine learning models for time-series and sequential data
  • Develop algorithms that extract structured signals and latent variables from noisy sensor inputs
  • Build and optimize real-time inference pipelines with latency and compute constraints
  • Explore and apply architectures such as:
  • Temporal convolutional networks (TCNs)
  • RNNs / LSTMs / GRUs
  • Transformer-based sequence models
  • Work on multi-modal learning and sensor fusion
  • Replace or augment classical signal processing pipelines with learned models
  • Design training strategies for:
  • Windowed and streaming data
  • Weakly labeled or partially observed datasets
  • Multi-task learning setups
    • Evaluate models using both statistical metrics and application-driven performance criteria
    • Collaborate with cross-functional teams to bring models from research to production

What You'll Bring (Qualifications)

  • Strong experience with machine learning for time-series data
  • Experience with Transfer learning and knowledge distillation techniques
  • Proficiency in Python and PyTorch (or similar frameworks)
  • Solid understanding of signal processing fundamentals (filtering, noise, frequency domain)
  • Experience working with real-world, noisy datasets
    • Experience building or deploying low-latency / real-time systems
  • Experience with sensor data (e.g., IMUs)
  • Familiarity with sensor fusion methods (e.g., Kalman filters, probabilistic models)
  • Experience with multi-modal or multi-task learning
  • Exposure to embedded or edge deployment constraints
  • Background in applied domains involving physical systems or human data
  • BSc or MSc degree in quantitative fields (e.g., computer science, engineering, physics, applied math)

Who You Are

  • Ability to reason about temporal structure, causality, and latency
  • Strong intuition for modeling tradeoffs vs. deployment constraints
    • Comfort working with imperfect, real-world data
    • End-to-end ownership: from modeling to validation to deployment
  • An Owner: You possess a powerful ownership mindset and take full accountability for your projects from concept to completion.
  • A Proactive Driver: You are a self-starter who can "catch the vision and run with it." You thrive with autonomy and are skilled at moving projects forward with minimal oversight.
  • A Team Player: You are a natural collaborator who communicates clearly and works effectively with cross-functional teams to achieve shared goals.
  • Adaptable and Resilient: You excel at managing multiple priorities without sacrificing quality. You see the challenges of a startup environment as opportunities.
  • Detail-Oriented: You have a keen eye for detail and are committed to producing high-quality, well-documented work.

Compensation, Benefits, Hours

This is a full-time employee position, working remotely or in our Los Angeles office. Compensation will be commensurate with experience and will be competitive with the market. You will also participate in the employee stock option program. You will be provided health care benefits (currently, gold PPO coverage with Blue Shield, as well as dental and vision) starting within 30 days of employment. We are an open PTO company. Occasional travel may be required domestically and internationally.

DISCLAIMER

We are an affirmative action, equal opportunity employer. Our employment decisions are made without regard to race, color, religion, gender, gender identity, national origin, age, disability, marital status, veteran or military status, or any other legally protected status. 

In accordance with the ADA, employees must perform the essential duties and responsibilities efficiently and accurately, with or without reasonable accommodation. The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and/or skills required of all personnel so classified. 

LI-DNI