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Full Time Recommender Systems Jobs (NOW HIRING)

Clera

Senior AI/ML Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Full-time, on-site in San Francisco. What you will do * Design and ship end-to-end ML systems: data ... Hands-on experience with LLMs, fine-tuning, RAG, or large-scale recommender systems * Strong Python ...

Astrion

$105K - $125K/yr

... Full-time CLEARANCE : MUST have an active TS/SCI at time of hire Astrion has an exciting ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

Headspace

Staff Machine Learning Engineer

$140K - $195K/yr

Our group builds conversational AI systems including Ebb, as well as search, recommendation ... The anticipated new hire base salary range for this full-time position is $140,400-$195,000 ...

Astrion

$104K - $115K/yr

... STATUS: Full-Time; Salaried SECURITY CLEARANCE: MUST have an active Secret security clearance ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

Abacus Technology

Systems Engineer

San Antonio, TX

This is a full-time position. * Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve systems engineering programs/processes, manage/sustain program technical ...

Astrion

Systems Engineer

Hanscom Air Force Base, MA · On-site

$104K - $115K/yr

... STATUS: Full-Time; Salaried SECURITY CLEARANCE: MUST have an active Secret security clearance ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

Astrion

$125K - $150K/yr

... JOB STATUS: Full-time CLEARANCE : TS/SCI TRAVEL: Limited, as needed Astrion has an exciting ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

Astrion

$125K - $150K/yr

... JOB STATUS: Full-time CLEARANCE : TS/SCI TRAVEL: Limited, as needed Astrion has an exciting ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

Astrion

$125K - $150K/yr

... JOB STATUS: Full-time CLEARANCE : Secret TRAVEL: Limited, as needed Astrion has an exciting ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

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Full Time Recommender Systems information

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$112K

$197K

How much do full time recommender systems jobs pay per year?

As of Aug 6, 2026, the average yearly pay for full time recommender systems in the United States is $111,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a recommender system?

Recommender systems are algorithms and software designed to suggest relevant items, such as products, movies, or content, to users based on their preferences and behavior. They are widely used in online platforms like e-commerce sites, streaming services, and social media to help users discover new items that match their interests. These systems use techniques such as collaborative filtering, content-based filtering, and hybrid approaches to analyze data and generate personalized recommendations. Full-time roles in recommender systems typically involve designing, building, and optimizing these algorithms to improve user engagement and satisfaction.

What are the key skills and qualifications needed to thrive as a full time recommender systems engineer?

To thrive as a Full Time Recommender Systems Engineer, you need a solid background in computer science, machine learning, and data analysis, usually supported by a relevant degree. Familiarity with tools such as Python, TensorFlow, PyTorch, and large-scale data processing systems like Spark is essential, along with experience implementing collaborative filtering, content-based, or hybrid recommendation algorithms. Strong problem-solving abilities, communication skills, and a collaborative mindset help you effectively translate business needs into technical solutions. These skills ensure the development of accurate, scalable, and user-focused recommendation systems that drive engagement and business value.

What are common challenges faced by professionals working full time on recommender systems, and how can they be addressed?

Full-time professionals in recommender systems often face challenges such as handling large-scale data, ensuring recommendation diversity, and mitigating biases in algorithms. Collaborating closely with data engineers, product managers, and UX designers is crucial to refine recommendations and align them with user needs. Staying updated with the latest research and regularly evaluating model performance helps in overcoming these challenges and maintaining system effectiveness. Many teams also use A/B testing and continuous feedback loops to iteratively improve recommendations.

What is the difference between Full Time Recommender Systems vs Data Scientist?

AspectFull Time Recommender SystemsData Scientist
CredentialsDegree in Computer Science, Data Science, or related fields; experience with machine learningDegree in Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentTech companies, e-commerce, streaming services focusing on recommendation algorithmsVarious industries including finance, healthcare, marketing, often involving data analysis and modeling
Industry UsagePrimarily in tech-driven sectors developing personalized recommendation systemsAcross multiple sectors analyzing data to inform business decisions

Full Time Recommender Systems specialists focus on developing and optimizing recommendation algorithms within tech companies, while Data Scientists analyze data across industries to support decision-making. Both roles require strong technical skills, but their primary focus and application environments differ.

More about Full Time Recommender Systems jobs
What cities are hiring for Full Time Recommender Systems jobs? Cities with the most Full Time Recommender Systems job openings:
What are the most commonly searched types of Recommender Systems jobs? The most popular types of Recommender Systems jobs are:
What job categories do people searching Full Time Recommender Systems jobs look for? The top searched job categories for Full Time Recommender Systems jobs are:
Full Time Recommender Systems jobs near you
Infographic showing various Full Time Recommender Systems job openings in the United States as of August 2026, with employment types broken down into 85% Full Time, 9% Part Time, 5% Contract, and 1% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $111,995 per year, or $53.8 per hour.

Senior AI/ML Engineer

Clera

San Francisco, CA • On-site

$123K - $169K/yr

Full-time

Re-posted 17 days ago

Job description

About the role
Our client is a well-funded AI startup building production-grade ML infrastructure used by enterprise customers. They are looking for a Senior AI/ML Engineer to own model training pipelines, evaluation systems, and inference serving at scale. Full-time, on-site in San Francisco.

What you will do

  • Design and ship end-to-end ML systems: data pipelines, training, evaluation, deployment

  • Own model performance, latency, and cost trade-offs in production

  • Build evaluation harnesses and offline benchmarks for fast iteration

  • Work directly with product to translate ambiguous goals into measurable model improvements

  • Mentor other engineers on ML best practices and code quality

What we are looking for

  • 4+ years of applied ML engineering in production environments

  • Hands-on experience with LLMs, fine-tuning, RAG, or large-scale recommender systems

  • Strong Python and PyTorch (or JAX) fundamentals

  • Experience with distributed training, GPU optimization, or inference serving

  • Pragmatic about trade-offs between research-grade and ship-grade work

This role is presented by a recruiting partner. Company name shared after an initial conversation.