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Ml Engineer Jobs (NOW HIRING)

DecisionPoint | Cortek

AI/ML Engineer

The AI/ML Engineer collaborates closely with data scientists, dashboard teams, developers, and PMO leadership to ensure AI/ML models are usable, optimized, and appropriately embedded into mission ...

Promantus, Inc

ML Engineer

Plano, TX · On-site

$110K - $132K/yr

This role is ML Engineering with hands-on software engineering skills using Python, PySpark, and Databricks. * Strong Python, Databricks, and PySpark experience with Spark, Kafka, Snowflake, MongoDB ...

Belva.ai

AI/ML Engineer

Bellevue, WA · On-site

As an AI / ML Engineer, you will work closely with our ML and Data Engineers to turn Machine Learning models and data pipelines into robust software applications. You will play a central role in ...

Whiz Global LLC

ML engineer

Jersey City, NJ · On-site

ML Engineer ## Key Responsibilities - Lead the end-to-end design, development, and deployment of scalable machine learning models and systems in production. - Architect robust, high-performance ML ...

Virtusa Corporation

ML Engineer

New York, NY · On-site

... engineering with 2+ years shipping ML models to production. - Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch). - Experience with containers and orchestration (Docker ...

Gainbridge

Staff ML Engineer

Zionsville, IN · On-site

$190 - $215/hr

As a Staff ML Engineer you'll focus on the MLOps and infrastructure layer that makes ML production‑ready: model serving, feature pipelines, experiment tracking and CI/CD for ML. You'll help shape ...

New

BTree Solutions, Inc.

AI/ML ENGINEER

Reston, VA · On-site

AI/ML ENGINEER Location: Reston,VA Duration: 12+ Months Visa: USC, GC, H1B and EAD Contract Type: W2 We are seeking a highly skilled and motivated AI/ML Engineer to join our team and drive the ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You'll help shape ...

Group1001

Staff ML Engineer

Zionsville, IN

As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You'll help shape ...

Vancor AI LLC

AI/ML Engineer

Austin, TX · On-site

$120 - $190/hr

Join Vancor AI as a AI/ML Engineer. You'll work on models, RAG pipelines, evaluation, and MLOps for enterprise workloads. You'll work with cross-functional teams to deliver secure, scalable solutions ...

New

Whiz Global LLC

ML engineer

Columbus, OH · On-site

ML Engineering role focused on building AI solutions and integrating them into the existing JPMorgan Chase ecosystem. * Work closely with Data Science teams and Subject Matter Experts (SMEs) to ...

Digital Links Inc

AI/ML Engineer

Minneapolis, MN · On-site

AI/ML Engineer Duration: 3-month contract (Could be extended for 6 months before conversion) Location: Minneapolis, MN (Remote/hybrid) Role Objective We are seeking a hands-on AI/ML Engineer to ...

Doist

AI/ML Engineer

Arlington, VA · On-site

$120 - $180/hr

540 is seeking an AI/ML Engineer to support a mission‑critical technology modernization effort for the Department of War. You will design, build, and maintain production AI/ML services and ...

New

Open Orion

ML Engineer

San Francisco, CA · On-site

They are seeking a strong ML Engineer to build agentic AI systems that reason about geometry and physics, develop generative models, and create systems for complex structured data. This role offers ...

Ruri Software Technologies LLC

ML Engineer

Irving, TX · On-site

Job Title: ML Engineer Work Location: Irving,TX (Hybrid) Duration: 8+ Months * Development and Implement data pipelines and ML pipelines to facilitate model inference (both Real-time and batch)

Docker, Inc

ML Engineer

They are seeking a ML Engineer to be a founding member of their Intelligence Org, focusing on building machine learning systems that enhance governance and security capabilities within the Docker ...

StoneGate-Technologies LLC

AI/ML Engineer

Austin, TX · On-site

Title: AI/ML Engineer Location: Austin, TX / Cupertino, CA Schedule: Hybrid (Tue Thu onsite, Mon & Fri remote) Contract: Longterm Note: Local candidates strongly preferred Start: Day 1 Onsite (No ...

New

Lululemon athletica

Staff AI/ML Engineer

Seattle, WA · On-site

Core responsibilities As a Staff AI/ML Engineer, you will define the Technology AI/ML engineering approach and solve complex model development, training infrastructure, and AI system reliability ...

Healthcare

ML Engineer

ML Engineer 3M Health Care is now Solventum At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our ...

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Ml Engineer information

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$33K

$89.2K

$142K

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.

AI/ML Engineer

DecisionPoint | Cortek

Remote

Full-time

Re-posted 14 days ago

Job description

Overview
DecisionPoint seeks an AI/ML Engineer to rapidly develop prototypes, implement integrations, and operationalize AI/ML capabilities that support a large federal and DoD-aligned mission environment. This role builds fast proofs-of-concept, API-based integrations, and lightweight user-facing components that validate new AI/ML ideas and help transition successful models into production dashboards and applications.
The AI/ML Engineer collaborates closely with data scientists, dashboard teams, developers, and PMO leadership to ensure AI/ML models are usable, optimized, and appropriately embedded into mission workflows.
This position is fully remote.
Duties & Responsibilities
The AI/ML Engineer will:
  • Develop rapid prototypes, microservices, APIs, widgets, and integrations to validate new AI/ML concepts.
  • Integrate ML models into dashboards, applications, and operational workflows.
  • Build lightweight UI components that demonstrate how AI outputs can be consumed.
  • Optimize ML pipelines for performance, scalability, and efficient inference.
  • Collaborate with AI/ML Architects and Data Scientists to operationalize models and automation logic.
  • Support data ingestion, feature engineering, and preprocessing tasks for prototype development.
  • Build API wrappers, routing logic, and connector services for ML model interactions.
  • Validate prototype functionality, performance, error handling, and model integration.
  • Contribute to documentation of models, prototypes, integrations, and deployment patterns.
  • Work with cybersecurity teams to ensure integration patterns align with security requirements.
  • Recommend improvements based on usability testing, technical feedback, and mission needs.

Qualifications
Clearance Requirement
Candidate must possess a Tier 2 Moderate Risk Public Trust (from any federal agency) or an active Secret clearance or higher.
Education (Required)
Bachelor's degree in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Statistics, or a related field.
Experience (Required)
  • Minimum 5 years of experience in software development, AI/ML engineering, or data-driven application development.
  • Experience building API-driven prototypes, integrations, or microservices.
  • Experience integrating ML models into dashboards, applications, or mission workflows.
  • Experience working with data scientists or ML engineers to transition models to production.

Technical Knowledge (Required)
  • Proficiency with Python, JavaScript, or similar development languages.
  • Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
  • Experience building REST APIs, web services, or integration layers.
  • Understanding of data pipelines, preprocessing steps, and ML lifecycle workflows.

Technical Knowledge (Preferred)
  • Experience with AWS cloud services or ML platforms.
  • Familiarity with front-end frameworks for rapid prototyping.
  • Experience with CI/CD pipelines and DevSecOps tooling.

Certifications
Required:
  • ITIL v4 Foundation

Preferred:
  • AI/ML engineering or cloud certifications
  • Scrum Master or Agile certifications

Skills
  • Strong development and prototyping skills.
  • Ability to translate AI/ML concepts into functional components quickly.
  • Strong collaboration skills with cross-functional technical teams.
  • Excellent communication and documentation skills.
  • High attention to detail in integration, testing, and optimization work.

Our Equal Employment Opportunity Policy
  • EEO and Affirmative Action Policy: DecisionPoint Corporation is an Equal Employment Opportunity and Affirmative Action employer. It is the policy of DecisionPoint Corporation to provide equal employment opportunity in accordance with all applicable Equal Employment Opportunity/Affirmative Action laws, directives and regulations to all employees and qualified applicants without regard to race, ethnicity, color, religion, national origin, sex, age, disability status, pregnancy, sexual orientation, gender identity, genetic information, protected veteran status, or any other protected status under Federal, State or Local laws.
  • Pay Transparency Policy: In accordance with Presidential Executive Order 13665, DecisionPoint Corporation will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
  • Authorization to Share Resume and Personal Information: By expressing your interest and submitting your resume for this position, you authorize DecisionPoint Corporation to share your resume, as well as personal information included on the resume, with its subsidiaries, affiliates and teaming partners for the purpose of considering you for this position and other available positions requiring comparable skills, education and experience. Should DecisionPoint Corporation. or its affiliates and teaming partners wish to initiate pre-employment discussions, you will be asked to complete an employment application and related employment documents.

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