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Full Time Recommender Systems Jobs (NOW HIRING)

Astrion

$105K - $131K/yr

... STATUS: Full-time; salaried CLEARANCE: Secret Clearance required 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

$105K - $115K/yr

... STATUS: Full-time; salaried CLEARANCE: Secret Clearance required Astrion has an exciting ... Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve ...

Astrion

Journeyman Systems Engineer

San Antonio, TX · On-site

$93K - $117K/yr

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

VAE, Inc.

Systems Administrator

Sierra Vista, AZ · On-site

Job Type Full-time Location Sierra Vista, AZ 85613 US (Primary) The Systems Administrator monitors ... Recommend changes in technologies and practices to improve these metrics. * Following a build ...

RiVidium, Inc

Systems Engineer (Senior)

Gordon, GA · On-site

$98K - $134K/yr

Full-Time/Part-Time Full-Time Description RiVidium Inc. is seeking an experienced Senior Systems ... recommend system improvements. Work Environment: * Requires Top Secret/SCI clearance . About the ...

Stride, Inc.

AI Architect

... recommender systems-across multiple product lines; * Leverages AWS and Azure ecosystems ... Directly supervises 1 - 3 Full-time Equivalent (FTE) regular employees and/or contractors. Carries ...

Astrion

$125K - $135K/yr

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

AGE Solutions LLC

Systems Engineer

Dayton, OH · On-site

... recommend corrective actions to improve performance and efficiency. • Administer enterprise ... onsite full-time at the client's location in Dayton, OH. • Must be able to work in a network ...

AGE solutions

Systems Engineer

Dayton, OH · On-site

Produce technical reports on storage management practices and emerging technologies; recommend ... Must be able to work onsite full-time at the client's location in Dayton, OH. Work Environment and ...

AGE Solutions

Systems Engineer

Dayton, OH · On-site

Produce technical reports on storage management practices and emerging technologies; recommend ... Must be able to work onsite full-time at the client's location in Dayton, OH. Work Environment and ...

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All JobsRecommender Systems JobsFull Time Recommender Systems Jobs

Full Time Recommender Systems information

See salary details

$46K

$112K

$197K

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

As of Jul 14, 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 are Recommender Systems?

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, and why are they important?

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 some 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 states have the most Full Time Recommender Systems jobs? States with the most job openings for Full Time Recommender Systems jobs include:
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 July 2026, with employment types broken down into 74% Full Time, 24% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $111,995 per year, or $53.8 per hour.

Senior Systems Engineer

Astrion

On-site

$105K - $131K/yr

Full-time

Posted 17 days ago

Job description

Overview

Senior Systems Engineer

LOCATION: Hanscom AFB, MA

Salary Range: $120-$130,000 annually*

*depending on experience, certifications, and qualifications

JOB STATUS: Full-time; salaried

CLEARANCE: Secret Clearance required

Astrion has an exciting opportunity for a Senior Systems Engineer to directly support the C3I & Networks Division (AFLCMC/HNI), which is within the Cyber & Networks Directorate and located at the Hanscom AFB, MA.

REQUIRED QUALIFICATIONS / SKILLS:

  • Education: Bachelor's Degree in a related field
  • Years of Experience: Ten years of experience in the respective technical / professional discipline being performed, five of which must be in the DoD. Two additional years of directly related experience with proper certifications may substitute for the Master’s degree. A total of 15 years of directly related experience (8 DoD) may substitute for the Bachelor's degree.
  • Current Required Security Clearance: DoD Secret clearance

  • Storage and virtualization experience is required.

RESPONSIBILITIES :

  • Conduct reviews on program portfolio to evaluate and/or recommend alternative plans, improve systems engineering programs/processes, manage/sustain program technical baseline, and design/perform system level tests to assure that subsystems and system performance is achieved in accordance with approved specifications.
  • Perform program reviews to evaluate alternative proposed plans, systems engineering programs, design, and test results to assure that subsystem and system performance is achieved in accordance with program specifications.
  • Prepare technical documents which define, specify, and recommend system/subsystem characteristics. Prepare management reports and conduct technical presentations for planning, implementation, and corrective action using application of engineering economy principles.
  • Perform validation of systems, including development of criteria and procedures. Analyze and/or evaluate results of major engineering systems.
  • Provide system/program engineering, technical support and technical training to support programs/initiatives, including but not limited to acquisition, development, integration, sustainment, continued evolution, deployment/fielding and installation, and operations oversight.
  • Provide engineering support services and inputs to program and project risk management activities in compliance with Air Force Systems Engineering Assessment Model (SEAM) processes.
  • Capable of performing problem/gap definition, trade space analysis, science and technology roadmap analysis, “Set based design” for concept development, Multi-Objective Decision Analysis and cost versus capability trade off analysis.
  • Capable of implementing Digital Engineering, Digital Thread, and Digital Twin techniques across system lifecycle.