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Machine Learning Engineer Jobs in Groton, CT (NOW HIRING)

Lead Engineer

Waterford, CT ยท On-site

$90 - $130/hr

Supervises represented engineers * Manages needed increases in capacity * Develops capital plan projects * Improves system reliability * Coordinates evaluation of system failures and resolutions

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Senior Engineer

Groton Long Point, CT ยท On-site

$103K - $142K/yr

Are you an experienced Senior Product Engineer with an expertise in Casting who enjoys solving problems? Are you self-driven with a commitment to implementing and leading change? At Doncasters we ...

GitHub Copilot, Claude, Cursor or ChatGPT) - Familiarity with AI directed prompt engineering for developing applications. Requirements: - Bachelor's degree or Diploma in Computer Science, Engineering ...

Lead Data Engineer

Carolina, RI ยท Remote

$115K - $138K/yr

We are seeking an experienced Lead Data Engineer to join our Data Platform Engineering Organization and lead the design, development, and modernization of enterprise data platforms that power ...

Lead Data Engineer

Carolina, RI ยท Remote

$115K - $138K/yr

We are seeking an experienced Lead Data Engineer to join our Data Platform Engineering Organization and lead the design, development, and modernization of enterprise data platforms that power ...

Submarine Senior Ship Design Engineer

Groton, CT ยท On-site

$103K - $142K/yr

This position provides systems engineering leadership across submarine design, platform integration, engineering governance, technical risk management, and complex engineering decision support. The ...

Showing results 41-60

Machine Learning Engineer information

See Groton, CT salary details

$31.3K

$128K

$192.4K

How much do machine learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning engineer in Groton, CT is $128,044.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,900.00 and $154,100.00 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 and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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 strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Groton, CT?

The most popular types of Machine Learning Engineer jobs in Groton, CT are:

What are popular job titles related to Machine Learning Engineer jobs in Groton, CT?

For Machine Learning Engineer jobs in Groton, CT, the most frequently searched job titles are:

What cities near Groton, CT are hiring for Machine Learning Engineer jobs?

Cities near Groton, CT with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Groton, CT as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,044 per year, or $61.6 per hour.

Senior Microsoft Cloud Engineer - Data Sharing & B2B

Applied Information Sciences

Groton, CT โ€ข On-site

$103K - $142K/yr

Full-time

Re-posted 13 days ago


Job description

Why AIS?

When you join AIS, you're joining a mission-driven team that's passionate about making a difference. You'll work on projects that matter, alongside industry-leading experts, in an environment that fosters innovation, driving client success, and empowering our team to make a lasting impact. As an employee-owned company, we value collaboration, inclusivity, continuous growth, and shared success.

  • Employee Ownership: Your contributions directly impact the company's success, and you share in its achievements.

  • Continuous Learning: Access to resources, training, and mentorship to support your professional growth.

  • Inclusive Culture: A workplace where diversity is celebrated, and everyone's voice is valued.

  • Mission-Driven Work: Engage in projects that make a meaningful difference for our clients and communities.

What are we looking for?

At AIS, we're looking for more than just skills - we're looking for driven individuals who are passionate about making a difference, eager to grow, and aligned with our core principles.

Working@AIS
At AIS, we are dedicated to providing our employees with diverse opportunities to grow their careers while supporting a variety of impactful projects. For this position, we are seeking a talented individual to join AIS as a Lead Infrastructure Engineer.
  • Core Knowledge & Skills: Aligns infrastructure strategy to business goals, leads large projects, applies compliance frameworks, designs high availability/disaster recovery and performance optimization patterns, and shapes deployment pipeline design.

  • Work & Complexity: Directs cross-team programs, performs advanced tuning, implements high availability/failover architectures, leads audits, plans growth, and manages budgets.

  • Quality & Independence: Delivers high-quality outcomes, sets team standards, introduces innovative solutions, and makes high-impact decisions.

  • Teamwork & Communication: Leads the engineering team, develops talent, resolves conflicts, and communicates effectively with senior leadership and stakeholders.

  • Consulting & Engagement: Provides high-level consulting to leadership, builds roadmaps, negotiates vendor contracts, and sponsors innovation initiatives.

As your initial project assignment, you will support the unique needs of our client as a Senior Microsoft Cloud Engineer - Data Sharing & B2B. Project Summary

AIS is seeking a Senior Microsoft Cloud Engineer to lead the design, implementation, and ongoing optimization of secure external collaboration capabilities across the Microsoft cloud ecosystem. This role is responsible for configuring and maintaining Azure B2B / Microsoft Entra External ID connections, implementing identity and data protection controls in Microsoft Entra and Microsoft Purview, designing secure access patterns for SharePoint-based extranets, and defining enterprise security controls for encrypted email, Conditional Access, Power Platform solutions, and Power BI content.

Key Responsibilities
  • Design, configure, andmaintainMicrosoft Entra B2B collaboration and cross-tenant access settings to support secure partner and guest access to enterprise applications, collaboration workloads, and external-facing business solutions.

  • Engineer and administer external identity controls including invitation workflows, trust settings, guest lifecycle processes, access reviews support, and secure onboarding/offboarding patterns for third-party users.

  • Design and implement security architecture for external access to SharePoint extranets, including authentication patterns, authorization boundaries,siteand content protection models, sharing restrictions, and monitoring requirements.

  • Define and implement Microsoft Purview Information Protection controls including sensitivity labels, encryption, data handling rules, and integration points with DLP and collaboration workloads.

  • Design and implement Microsoft Purview Message Encryption and related encrypted mail protections for secure communication with external recipients, including policy-based encryption use cases and operational support models.

  • Design, test, and tune Conditional Access policies to govern external access based on user, device, application, session, location, risk, and authentication context, using phased rollout and validation practices.

  • Build secure access patterns for Power Platform applications, flows, and connectors through environment strategy, role design, data policies, connector governance, and identity controls.

  • Define and implement security controls for Power BI reports, dashboards, semantic models, workspaces, sharing models, and external consumption scenarios.

  • Partner with security, compliance, messaging, collaboration, and application teams to translate policy and regulatory requirements into enforceable cloud controls.

  • Produce architecture diagrams, standards, control narratives, engineering runbooks, and operational procedures for steady-state support.

Required For This Opportunity
  • 8+ years of experience in Microsoft cloud engineering, with substantial hands-on responsibility for Microsoft 365, Azure, and enterprise security controls.

  • 4+ years of direct experience designing and administering Microsoft Entra ID / Azure AD identity and access solutions.

  • Deep experience with Microsoft Entra External ID / B2B collaboration, cross-tenant access, external collaboration settings, guest access governance, and secure partner access models.

  • Strong experience implementing Microsoft Purview Information Protection capabilities, including sensitivity labels, encryption, and data protection policy integration.

  • Strong experience designing Microsoft Purview Message Encryption / OME solutions for secure external email exchange.

  • Proven experience designing and deploying Conditional Access policies in enterprise environments, including policy testing, exception handling, and access hardening.

  • Experience securing SharePoint Online sites and extranets for external access, including site permissions, sharing models, and information protection considerations.

  • Experience implementing governance and security controls for Power Platform, including environment strategy, roles, and data policies.

  • Experience securing Power BI platforms, including workspace governance, dataset security, sharing controls, and report access design.

Nice to Have Skills
  • Experience in highly regulated environments such as defense, government, healthcare, financial services, or other compliance-driven enterprises.

  • Experience supporting security assessments, accreditation packages, or control inheritance models.

  • Familiarity with Microsoft Defender, audit logging, insider risk considerations, andmonitoring ofcollaboration and sharing events.

  • Experience with DevOps,infrastructure ascode, or scripted administration using PowerShell, Microsoft Graph, or automation tooling.

  • Microsoft certifications in areas such as Microsoft Entra, Microsoft 365 Security, Azure Security, or Purview.

At AIS, we are committed to offering competitive and fair compensation that reflects the skills, experience, and contributions of each team member. The targeted base salary range for this role is $121,000-$182,000 per year. Please note that this range is provided as a guideline and the final offer will be based on several factors, including but not limited to, skillset and competencies, level of experience, education, certifications, and location. We value transparency in our hiring process and are happy to discuss how your unique qualifications align with our compensation structure during the interview process.

Applied Information Sciences does not discriminate on the basis of race, national origin, religion, color, gender, sexual orientation, age, disability, protected veteran status, or any other basis. Employment decisions are based solely on qualifications, merit, and business needs.