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Machine Learning Engineer Opt Jobs in Albany, NY

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

AI/ML Engineer Location : Remote We are currently seeking candidates who meet the following ... Develop, train, and deploy machine learning and deep learning models for classification, prediction ...

Collaborate with product and engineering teams to integrate machine learning solutions into production systems * Stay current with emerging trends in data science, machine learning, and AI to ...

Data Engineer

Albany, NY · Hybrid

$100K - $110K/yr

Interaction with stakeholders such as data governance workgroups, machine learning engineers, integration data pipeline builders, and BI developers is a key aspect of the role. The role involves ...

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Machine Learning Engineer Opt information

See Albany, NY salary details

$31.3K

$127.9K

$192.1K

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

As of Sep 4, 2026, the average yearly pay for machine learning engineer opt in Albany, NY is $127,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $153,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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 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.

What are popular job titles related to Machine Learning Engineer Opt jobs in Albany, NY?

For Machine Learning Engineer Opt jobs in Albany, NY, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Opt jobs in Albany, NY look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Albany, NY are:

What cities near Albany, NY are hiring for Machine Learning Engineer Opt jobs?

Cities near Albany, NY with the most Machine Learning Engineer Opt job openings:

Infographic showing various Machine Learning Engineer Opt job openings in Albany, NY as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $127,851 per year, or $61.5 per hour.

Machine Learning Engineer

Kitware

Clifton Park, NY

$85K - $125K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 27 days ago


Key responsibilities

  • Collaborate with researchers on projects related to machine learning, artificial intelligence, and computer vision

  • Perform rapid prototyping and enhanced development to be integrated into operational systems

  • Validate, optimize, and deploy advanced exploitation algorithms


Job description

Team Description:
Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI), spanning computer vision (CV), natural language processing (NLP), vision-language models (VLMs), and other generative AI technologies. Our solutions embracing AI add measurable value to government agencies, commercial organizations, and academic institutions worldwide. We have developed a deep understanding in extracting useful, actionable information from multiple data sources like images, video, metadata, audio, and text, and we recognize the need for robust, affordable solutions. We seek to advance AI, CV, and other related fields through research and development and collaborative projects that can contribute to our open source software platforms, such as XAITK, NRTK, and GeoWATCH.
 
About the Projects: 
Kitware’s employees have unique opportunities to interact and collaborate directly with customers, visit interesting customer sites, and participate in live field tests and demonstrations. Much of Kitware’s work involves applying state-of-the-art artificial intelligence approaches to dynamic, real-world problems. We consider the work that we do on our government contracts as one of the ways that we give back to the community. We partner with premier government R&D agencies such as DARPA, IARPA, AFRL, Army C5ISR, NOAA, and other branches of the US Government on a range of efforts, including prime contracts, SBIRs, and STTRs. In addition, we provide commercial services to companies ranging from startups to Fortune 500 companies. Kitware employs an open source business model to foster extended, collaborative communities and to provide effective, flexible, and high-quality technical solutions.
In This Position You Will:
  • Collaborate with researchers on projects related to machine learning, artificial intelligence, and computer vision 
  • Perform rapid prototyping and enhanced development to be integrated into operational systems
  • Contribute your strong programming ability and experience to develop robust solutions for real-world problems
  • Validate, optimize, and deploy advanced exploitation algorithms
  • Perform troubleshooting, bug fixes, and maintenance of existing and new code to ensure stability and robustness
Required Qualifications:
  • Bachelor's degree or Master's degree in Computer Science, Electrical and Computer Engineering, or related field
  • Proficiency in Python
  • Experience with deep learning libraries (PyTorch, TensorFlow, etc.)
  • Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment
  • Machine learning experience using visual data
  • Understanding of a variety of machine learning tasks, e.g. Object Detection, Segmentation, Re-Identification, Tracking, Pose, Super Resolution, Natural Language Processing
  • A high level of comfort with academic literature and the ability to adapt research products to solve real-world problems
  • Due to contractual requirements, only US Citizens will be considered for this position
  • If not already cleared TS/SCI, willingness and ability to apply for and maintain a TS/SCI security clearance
  • Some travel is required, typically 5-25%
  • Full-time on-site work at the Kitware Office
Preferred Qualifications:
  • Active SECRET, TS, or TS/SCI security clearance
  • Experience curating quality, real-world datasets for training deep learning models
  • Proficiency in C++
Company Description:
Kitware is a research and development software solutions provider with a mission to advance science, make a positive impact, and share our results all within a collaborative, employee-focused work environment that is friendly, fair, and flexible. Our work is improving healthcare outcomes, increasing national security, and advancing our national computing infrastructure. Our customers and collaborators include top universities from around the world, government organizations, national research labs, medical device manufacturers, car manufacturers, financial institutions, and many others.  
 
Kitware is proud to be 100% employee-owned, and Great Place to Work-Certified™.  
 
Additional Information:
Our team members enjoy a small company environment, flexibility in work assignments, and high levels of independence and responsibility. Besides a great work environment, our comprehensive benefits package includes a competitive compensation plan, tuition reimbursement program, flexible working hours, six weeks paid time off, 401(k), health insurance, life insurance, short- and long-term disability insurance, bonus plan, and free coffee, drinks, and snacks. 
 
For more information on our benefit offerings please visit: https://www.kitware.com/careers/.
 
Kitware actively subscribes to a policy of equal employment opportunity. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, age, protected veteran status, uniformed service member status, or any other characteristics protected by applicable law. 
 
Any unsolicited resume sent to Kitware, including to Kitware's mailing addresses, fax machines or email addresses, whether directly to Kitware employees or to Kitware's applicant tracking system, will be considered Kitware property.  Kitware will not pay a fee for any placement resulting from the receipt of an unsolicited resume, and will consider any candidate submitted by a recruitment agency without a fully executed contract with Kitware to have been referred free of any charges or fees.
 
If you need assistance with applying or interviewing for a role due to a disability or special need, please reach out directly to our HR team at hr@kitware.com at any time during the hiring process.  

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.