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Remote Machine Learning Engineer Jobs in North Hollywood, CA

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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 Aug 22, 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:

Remote Machine Learning Engineer jobs near you
Infographic showing various Remote Machine Learning Engineer job openings in North Hollywood, CA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Contract, and 3% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $135,655 per year, or $65.2 per hour.

Staff Machine Learning Engineer

Prodege LLC

El Segundo, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, PTO

Posted 25 days ago

Job description

Job Description:
Read this part first:
This is a role for someone who wants to solve hard machine learning problems by building production systems that matter.
We're looking for a Staff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and the business to deliver measurable outcomes.
This is a deeply hands-on individual contributor role. You'll spend the majority of your time building, deploying, experimenting with, and improving production machine learning systems, not managing people or operating primarily at the architectural strategy level.
If you enjoy taking ownership of difficult ML problems, iterating quickly through experimentation, and seeing your work directly improve revenue, marketplace efficiency, and customer experience, this role is for you.
You'll build production ML systems for a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, powered by a data platform with 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics supporting both batch and real-time workflows.
Prodege:
A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.
As an organization, we go the extra mile to "Create Rewarding Moments" every day for our partners, consumers, and team. Come join us today!
What you'll own
  • Design, build, and operate production machine learning systems from development through deployment
  • Production models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization
  • Feature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement
  • Reliable production ML practices including testing, observability, retraining, and model health
  • Technical leadership through code reviews, collaboration, and mentoring less experienced engineers
  • Cross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems

What makes this role exciting
  • You'll work on machine learning problems that directly impact revenue, marketplace efficiency, and customer experience.
  • You'll own production systems-not just models-from experimentation through deployment and optimization.
  • You'll build on top of a production platform processing 50M daily events, 500M daily pipeline records, and a 100TB Iceberg lake.
  • You'll join a team with an active experimentation culture, shipping ML improvements that quickly reach production.
  • You'll have significant ownership while partnering with senior technical leaders to shape the future of ML at Prodege.
  • You'll work in an engineering culture embracing AI-assisted development to improve productivity and accelerate experimentation.

What you'll do
  • Design, build, deploy, and maintain production machine learning systems.
  • Develop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation.
  • Improve feature engineering, model performance, inference latency, and operational reliability.
  • Design and analyze offline evaluations and A/B experiments to validate business impact.
  • Partner with Data Engineering to build reliable data pipelines and feature sets for ML.
  • Contribute to MLOps practices including deployment, monitoring, retraining, and model lifecycle management.
  • Review code, mentor teammates, and help raise engineering quality across the ML organization.
  • Leverage AI-assisted development to accelerate research, prototyping, debugging, documentation, and experimentation.

What you'll bring (must-haves)
  • 6+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related technical fields.
  • 3+ years building, deploying, and operating production machine learning systems.
  • Strong experience building production recommendation, ranking, personalization, optimization, or prediction systems.
  • Experience working in AdTech, MarTech, Growth, Consumer Products, Marketplace platforms, or adjacent domains.
  • Strong understanding of:
    • Feature engineering
    • Offline and online inference
    • Experimentation and A/B testing
    • Model serving
    • Monitoring and retraining
    • MLOps best practices
  • Experience partnering closely with Product, Engineering, and Data teams to deliver measurable business outcomes.
  • Strong software engineering fundamentals with excellent coding skills.
  • Comfort operating in ambiguous environments while independently driving technical solutions.
  • Demonstrated ability to mentor engineers and influence technical decisions across teams.

Bonus points
  • Experience with ROAS optimization, bidding systems, rewards platforms, or monetization models.
  • Experience with streaming or near-real-time ML systems.
  • Experience with recommendation engines or personalization at scale.
  • Experience using feature stores or shared ML infrastructure.
  • Experience with causal inference, uplift modeling, or counterfactual reasoning.
  • Master's degree or PhD in Machine Learning, AI, Computer Science, or a quantitative discipline.
  • Experience using AI-assisted development tools in software engineering workflows.

Pay Transparency:
The anticipated base salary range for this position is $240,000 to $290,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Prodege Benefits:
Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.
Equal Employment Opportunity Statement
At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.
FCIHO
Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

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