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Ml Engineer Jobs (NOW HIRING)

TiltEdge Solutions LLC

ML Engineer

Plano, TX · On-site

$35/hr

ML Engineer Location: Plano, TX (onsite) Need local candidates only, F2F interview * This role is ML Engineering with hands-on Software Engineering skills using Python and Pyspark, Databricks.

New

Compunnel

ML Engineer

Aliso Viejo, CA · On-site

ML Engineer I JOB SUMMARY Under guidance from Senior ML Engineers, develop ML models that provides accurate results with controls to solve the business problem identified, using state of art ...

Whiz Global LLC

ML Engineer

Columbus, OH · On-site

ML Engineer (AI/LLM & Cloud) Location: Jersey City, NJ (Hybrid - 3 Days Onsite) OR Columbus, OH (5 Days Onsite) Duration: Contract-to-Hire Job Summary We are seeking a highly experienced ML Engineer ...

Catalyst Labs

ML Engineer

Manhattan Beach, CA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Manhattan, NY · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Palo Alto, CA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

San Francisco, CA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Stamford, CT · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Manhattan, NY · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Chicago, IL · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Miami, FL · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

San Jose, CA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Sunnyvale, CA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Charlotte, NC · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Austin, TX · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Houston, TX · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Cupertino, CA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

San Antonio, TX · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Seattle, WA · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, while collaborating with cross-functional teams to drive innovation in AI applications. Responsibilities ...

Catalyst Labs

ML Engineer

Tampa, FL · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

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Ml Engineer information

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$33K

$89.2K

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How much do ml engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ml engineer in the United States is $89,183.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $109,000.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.

What does a machine learning engineer do?

A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.
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Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $89,183 per year, or $42.9 per hour.

ML Engineer

TiltEdge Solutions LLC

Plano, TX • On-site

$35/hr

Contractor

Posted 3 days ago

New

Job description

Job Title: ML Engineer
Location: Plano, TX (onsite)
Need local candidates only, F2F interview
Job Description:

  • This role is ML Engineering with hands-on Software Engineering skills using Python and Pyspark, Databricks.
  • Strong Python, Databricks and PySpark experience with Spark, Kafka, Snowflake, MongoDB, PostgreSQL, Redis, Azure cloud.
  • Advanced No-SQL (MongoDB) and SQL (Postgres) and data modeling for slowly changing dimensions / temporal mappings. Experience building production-grade ML pipelines, and data pipelines.
  • Solid Python development skills with APIs development (FastAPIs) and familiarity with ML workflows.
  • Delta Lake, MLflow, and workflow orchestration experience.
  • Agentic development and GenAI experience will be a big plus
  • Familiarity with ELK (Elastic Kibana)
  • Please note that DE with GenAI knowledge will not be shortlisted;
  • The candidate must have classical ML/DS exposure with production pipeline design and development experience.