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Machine Learning Engineer Opt Jobs (NOW HIRING)

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Purple Drive

Machine Learning Engineer

Newark, NJ · On-site

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Samprasoft

Machine Learning Engineer

Mclean, VA · On-site

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

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Machine Learning Engineer Opt information

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$31.5K

$128.8K

$193.5K

How much do machine learning engineer opt jobs pay per year?

As of Jun 23, 2026, the average yearly pay for machine learning engineer opt in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
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Machine Learning Engineer Opt jobs near you
Machine Learning Engineer

Machine Learning Engineer

Compunnel

Plano, TX • On-site

Contractor

Posted 22 days ago

Job description

Job Summary
We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus on building ML-ready data architectures, developing scalable machine learning solutions, and supporting enterprise analytics initiatives. The ideal candidate will possess hands-on experience with Azure Databricks, Python-based model development, Medallion Architecture, and MLOps practices, along with the ability to collaborate effectively with business and technical stakeholders.
Key Responsibilities
  • Design, develop, and maintain machine learning solutions that support advanced analytics and predictive modeling initiatives.
  • Build and optimize ML-ready data pipelines and data architectures using Medallion Architecture principles.
  • Develop and manage data ingestion, transformation, and curation processes across Bronze, Silver, and Gold data layers.
  • Create scalable feature engineering workflows and production-grade machine learning assets.
  • Design and implement machine learning pipelines using Azure Databricks and related cloud technologies.
  • Leverage Delta Lake, MLflow, and workflow orchestration tools to operationalize machine learning models and data transformations.
  • Develop and maintain Python-based machine learning models, feature engineering processes, and MLOps automation solutions.
  • Build and optimize SQL transformations, views, and ELT pipelines to support analytics and machine learning workloads.
  • Design and maintain feature stores, semantic layers, and curated datasets that support enterprise reporting and machine learning initiatives.
  • Integrate machine learning outputs into analytics platforms, dashboards, and business intelligence solutions.
  • Collaborate with business stakeholders, technical teams, and leadership to translate business requirements into scalable data and machine learning solutions.
  • Establish engineering standards, best practices, and scalable development processes for machine learning and data engineering initiatives.
  • Monitor data quality, model performance, and operational effectiveness of machine learning solutions.

Required Qualifications
  • 5-7 years of hands-on experience in machine learning engineering and data engineering.
  • 10+ years of experience delivering enterprise-scale data, analytics, and machine learning solutions.
  • Strong experience building machine learning models and supporting model development using Python.
  • Extensive experience with Azure Databricks for machine learning, feature engineering, and data engineering workloads.
  • Deep understanding of Medallion Architecture, including Bronze, Silver, and Gold data layer design and implementation.
  • Experience designing ML-ready data architectures and scalable data engineering solutions.
  • Experience migrating workloads to Databricks and implementing modern data platform architectures.
  • Hands-on experience with Delta Lake, MLflow, and Databricks Workflows.
  • Strong proficiency in Python for model development, feature engineering, and MLOps automation.
  • Advanced SQL skills with experience building optimized transformations, views, and ELT pipelines.
  • Experience designing feature stores, semantic models, and machine learning-ready datasets.
  • Strong understanding of machine learning lifecycle management, data engineering best practices, and scalable architecture patterns.
  • Ability to lead technical initiatives and establish engineering standards and development practices.
  • Strong business acumen and ability to communicate effectively with technical and business stakeholders.
  • Experience working in collaborative, fast-paced environments that encourage experimentation and innovation.

Preferred Qualifications
  • Experience working within Microsoft Azure cloud environments.
  • Experience integrating machine learning outputs into analytics platforms and business intelligence solutions.
  • Experience designing dashboards and reporting solutions that surface machine learning insights, data quality metrics, and model performance indicators.
  • Familiarity with Power BI, including DAX, semantic modeling, and visualization best practices.
  • Experience supporting enterprise-scale analytics, data science, and AI initiatives.
  • Experience mentoring technical teams and providing technical leadership on machine learning and data engineering projects.
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About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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