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Machine Learning Engineer Opt Jobs in Connecticut

Purple Drive Technologies

Senior AI Engineer

Hartford, CT · On-site

$55.75 - $71.75/hr

You will work closely with Cloud and Machine Learning engineers, as well as the CRM development team to ensure the proper integration of AI technologies into the platform. You will be responsible for ...

Purple Drive Technologies

Senior AI Engineer

Hartford, CT · On-site

$55.75 - $71.75/hr

You will work closely with Cloud and Machine Learning engineers, as well as the CRM development team to ensure the proper integration of AI technologies into the platform. You will be responsible for ...

Deloitte

Senior AI Engineer - SFL Scientific

Stamford, CT

$111.40K - $153K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

NAVA Software Solutions

Senior Data Engineer

Bloomfield, CT · On-site

$105.90K - $143.90K/yr

Senior Data Engineer Location: Bloomfield, CT; Denver, CO; Austin, TX; NYC, NY; virtual work is ... Understanding of Machine learning frame works (e.g. Scikit learning, Scipy) * Understanding and 1+ ...

Deloitte

AI and Data Science Engineer III

Stamford, CT · On-site +1

$122.10K - $146.60K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

Deloitte

AI Data Engineer - Manager

Hartford, CT

$115.50K - $138.70K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

Deloitte

AI and Data Science Engineer III

Hartford, CT · On-site +1

$115.50K - $138.70K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

Deloitte

AI Data Engineer - Manager

Stamford, CT

$122.10K - $146.60K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

Deloitte

Senior AI Engineer - SFL Scientific

Stamford, CT · On-site

$111.40K - $153K/yr

Deloitte's Strategy & Transactions team is seeking a Senior AI Engineer to join SFL Scientific, a ... machine learning applications. Responsibilities : • Work with clients to design, develop, and ...

New

Deloitte

AI Data Engineer Senior Consultant

Stamford, CT · On-site

$122.10K - $146.60K/yr

They are seeking an AI Data Engineer Senior Consultant to build and operate the data, features, and ... machine learning training and real-time inference, including online and offline consistency ...

Deloitte

AI Data Engineer Senior Consultant

Hartford, CT · On-site

$115.50K - $138.70K/yr

They are seeking an AI Data Engineer Senior Consultant to build and operate the data, features, and ... machine learning training and real-time inference, including online and offline consistency ...

Pwc

CTIO AI Engineering Manager

Stamford, CT

$73.50K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Machine Learning Engineer Opt information

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.

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 popular job titles related to Machine Learning Engineer Opt jobs in Connecticut? For Machine Learning Engineer Opt jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Connecticut look for? The top searched job categories for Machine Learning Engineer Opt jobs in Connecticut are:
What cities in Connecticut are hiring for Machine Learning Engineer Opt jobs? Cities in Connecticut with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you

Senior AI Engineer

Purple Drive Technologies

Hartford, CT • On-site

$55.75 - $71.75/hr

Full-time

Posted 11 days ago

Job description

Overview:
Summary
As an AI engineer, you will be in charge of designing and implementing AI capabilities for a Contact Center platform in a Healthcare Payer enterprise. You will work closely with Cloud and Machine Learning engineers, as well as the CRM development team to ensure the proper integration of AI technologies into the platform. You will be responsible for the strategy, design, implementation, and maintenance of AI solutions.
This role requires a highly skilled professional with a deep understanding of AI technologies and the ability to collaborate effectively with a diverse team. The ideal candidate will have a strong background in data science and a proven track record in the industry.
Responsibilities
  • Design and develop AI applications and infrastructure for the Contact Center platform.
  • Collaborate with Cloud and Machine Learning engineers, as well as the development team to ensure seamless integration of AI technologies.
  • Stay current with the latest AI trends and technologies, especially Google GCP or Azure AI for Contact Center
  • Create and maintain AI models and algorithms.
  • Conduct AI research to improve existing systems and develop new technologies.
  • Identify opportunities for AI solutions within the organization and propose strategic plans.
  • Train team members and stakeholders on AI and its applications.
  • Ensure compliance with data privacy regulations in AI applications.
  • Monitor the performance of AI systems and make necessary adjustments.
  • Experience in agentic architecture-based implementations and advanced Retrieval Augmented Generation.

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