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Machine Learning Engineer Opt Jobs in Connecticut

The Hartford

AI Machine Learning Engineer

Hartford, CT · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Bespoke Labs

Machine Learning Engineer

New Haven, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Hamden, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Norwalk, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Hartford, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Waterbury, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Bridgeport, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Danbury, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Stamford, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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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.

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 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.
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Machine Learning Engineer Opt jobs near you
Machine Learning Engineer

Machine Learning Engineer

Graham Capital Management, L.P.

Norwalk, CT • On-site

Full-time

Posted 27 days ago

Job description

Job Summary:
Graham Capital Management, L.P. is an alternative investment manager specializing in discretionary and quantitative macro strategies. They are seeking a Machine Learning Engineer to join their Data Science team, where the role involves developing innovative solutions using machine learning and advanced statistical methods to support quant strategies and enhance data insights for stakeholders.
Responsibilities:
• You will be part of a growing team within Data Science.
• You will work alongside world-class talent to find innovative solutions to some of the most interesting problems in the buy-side.
• You will work closely with other areas such as Technology, Quantitative Research and Portfolio Manager groups as well as Risk and Operations to learn about problems they face with respect to data and ultimately develop cutting edge solutions.
• Your focus will be to dive deep into multiple data sets to understand relationships, develop time series, forecasting models, and support quant strategies, and provide new insights and leverage state-of-the-art machine learning and advanced statistical methods to produce the best data sources for the fund.
Qualifications:
Required:
• Undergraduate or higher degree in Computer Science, Engineering, Operations Research, or other quantitative discipline
• 3+ years of hands-on experience with Machine Learning and Statistics on large, unstructured, data sets
• Experience writing production code for multi-client systems serving model results is a great plus
• Ability to clearly communicate research findings to technical and nontechnical stakeholders
• Full-stack experience with Python (preferred) or C++, Spark/Scala, SQL or other distributed data processing technologies as well as experience working comfortably building and deploying services and models in containerized environments
• Experience with scientific computing, statistics, optimization, time series, panel data, etc.
• Comfortable handling multiple projects to solve varied problems working with multiple teams
• Detail-oriented mindset
• Sense of ownership of his/her work, working well both independently as well as collaboratively
Company:
Who We Are & What We Do: Graham Capital Management, L.P. Founded in 1994, the company is headquartered in Norwalk, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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