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Machine Learning Engineer Opt Jobs in Ohio (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Akron, OH · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Columbus, OH · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Cleveland, OH · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Cincinnati, OH · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Diverse Lynx

ML Engineering Delivery

Cincinnati, OH

Machine Learning Engineer Machine Learning Engineering Delivery Location: Blue Ash, OH Competencies: 10+ years experience required Agile Way of Working Digital: Machine Learning Digital: Artificial ...

SCATR Corp.

Artificial Intelligence Engineer

Cleveland, OH

$111K - $133K/yr

As an AI Engineer, you will be responsible for designing, implementing, testing and maintaining ... The ideal candidate will have a strong background in AI, machine learning and data science, with ...

Eliassen Group

Senior AI/ML Engineer

Columbus, OH · Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

SynergisticIT

AI Engineer - Junior

Cleveland, OH

... OPT/H4EAD/L2EAD) who want to get employed and settle down in the USA. Please check the below links ... Excellent written and verbal communication skills For Data Science/Machine Learning: * Bachelors ...

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Machine Learning Engineer Opt information

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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What job categories do people searching Machine Learning Engineer Opt jobs in Ohio look for? The top searched job categories for Machine Learning Engineer Opt jobs in Ohio are:
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Machine Learning Engineer Opt jobs near you

AI Staff Machine Learning Engineer -Gen AI,Machine Learning,Graph ML,Big Data(10030)

Extreme Networks

New Hampshire, OH

Full-time

Posted 22 days ago

Job description

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.

Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.

Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team.

Position : AI Staff Machine Learning Engineer -Gen AI,Machine Learning,Graph ML,Big Data
Experience : 5 to 14 Years
Hybrid/Remote
 
Our AI Core group is pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship Extreme products while enabling entirely new offerings. Together, we are driving a fundamental shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Extreme, innovation is not just encouraged, it is expected. Advance with us and help shape the future of network intelligence. 
About the position
  • Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic machine learning (ML) solutions and drive business-wide innovation.
  • Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy, and participate hands-on in design reviews, code reviews, and implementation.
  • Craft high-performance, high-scale microservices architectures, including synchronous and asynchronous web services.
  • Develop real-time online inferencing for highly complex models using Triton, TensorRT and mixed precision computing.
  • Mentor and develop other engineers on the team, establish technical direction and foster team culture.
  • Uphold the highest standards of technical rigor in engineering and operational excellence, build highly resilient and scalable systems, and champion operational and process improvements.
Basic Qualifications:
  • Degree in mathematics/computer science or related discipline.
  • 5 to 10 years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
  • 5 to 10 years of experience in Python with an in-depth knowledge of its advanced features and libraries.
  • Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI.
  • Proficient in Docker, Kubernetes, and modern CI/CD practices.
  • 3+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Experience as a mentor, tech lead or leading an engineering team.
Preferred Qualifications:
  • MS or PhD in Computer Science or equivalent experience in ML.
  • Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.).
  • Experience with NoSQL and document databases.
  • Proven ability to handle big data, optimize workflows, and improve system performance.
  • Come work with a team of highly talented engineers, and advance with us to achieve new heights every day!
 
  • Salary based on qualifications, experience and region up to USD 170 k to 240 K plus benefits.
Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.

We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on “protected categories,” Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.