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Embedded Machine Learning Jobs in Connecticut (NOW HIRING)

Gartner, Inc.

Director, Data Science

Stamford, CT · On-site

Our clients are IT and business leaders worldwide, relying on the platform embedded in their ... What You Will Need * 8-12 years of experience in data science, machine learning, or AI, with at ...

TicketNetwork

Director of Data and AI

South Windsor, CT · On-site

... embedded into systems and workflows, preventing bad data at the source rather than correcting it ... Generative AI, machine learning, and advanced analytics * Enterprise data and analytics platforms

Gartner

Director, Data Science

Stamford, CT · On-site

Our clients are IT and business leaders worldwide, relying on the platform embedded in their ... What You Will Need * 8-12 years of experience in data science, machine learning, or AI, with at ...

Gartner

Director, Data Science

Stamford, CT · Remote

Our clients are IT and business leaders worldwide, relying on the platform embedded in their ... What You Will Need * 8-12 years of experience in data science, machine learning, or AI, with at ...

Henpen Corporation

Power Electronics Engineer

Groton, CT · On-site

$111K - $131K/yr

... embedded processors is required. Previous experience laying out boards and/or managing layout ... opportunities and learning experiences. You will work in a small company environment where ...

Henpen Corporation

Power Electronics Engineer

Groton, CT

$111K - $131K/yr

... embedded processors is required. Previous experience laying out boards and/or managing layout ... opportunities and learning experiences. You will work in a small company environment where ...

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Embedded Machine Learning information

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are the most commonly searched types of Embedded Machine Learning jobs in Connecticut? The most popular types of Embedded Machine Learning jobs in Connecticut are:
What are popular job titles related to Embedded Machine Learning jobs in Connecticut? For Embedded Machine Learning jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Connecticut look for? The top searched job categories for Embedded Machine Learning jobs in Connecticut are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Connecticut as of June 2026, with employment types broken down into 92% Full Time, and 8% Part Time. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.
AVP Applied AI, Claims

AVP Applied AI, Claims

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site

Full-time

Posted 6 days ago

The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 109 frontline employees who took The Breakroom Quiz

48th of 277 rated insurance

Job description

AVP Data Science - GD05AE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.
The Hartford is hiring an AVP leading Applied AI for the Claims organization. This leader will play a pivotal role in transforming the end-to-end Claims process by developing and embedding AI capabilities to enhance outcomes, process and experience.
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week. Candidates must be eligible to work in the US without company sponsorship.
Primary Job Responsibilities
  • Own delivery, performance, and risk outcomes for a large, complex Claims Applied AI portfolio spanning multiple teams, domains, and value streams; translate Claims and enterprise AI priorities into a multi-year roadmap and investment plan.
  • Drive measurable business value across the end-to-end claims journey by developing, testing, deploying, and scaling Predictive, Generative, and Agentic AI solutions (e.g., forecasting, triage, recommendations, anomaly/fraud detection, RAG/assistants, and agentic workflow orchestration).
  • Be the senior business partner for Claims leaders: proactively understand short- and long-term goals, shape the problem statements, define success measures, and ensure solutions are adopted and embedded into core claim processes and colleague experiences.
  • Build deep partnerships within portfolio and value stream frameworks; promote agile, iterative delivery through cross-functional teams to ensure fit-for-purpose solutions and rapid learning cycles.
  • Lead and develop senior leaders and teams (e.g., asset owners, data engineers, data scientists, ML engineers), building bench strength through succession planning, coaching, and capability development while creating an engaged and inclusive culture
  • Provide portfolio-level technical direction and oversight, partnering with Principal Individual Contributors, Architecture, AI Platform, and Centers of Excellence to drive consistent adoption of approved standards, patterns, and guardrails
  • Ensure disciplined architecture and delivery trade-offs across quality, grounding, latency, cost, scalability, and regulatory risk-especially for GenAI and agentic solutions operating in claims environments.
  • Establish and enforce evaluation, monitoring, and production readiness across solution types (classification, regression, retrieval/RAG/chat, forecasting), including metric taxonomies, thresholds, validation evidence, gold/synthetic test sets, A/B testing, drift detection, failure mode analysis, and incident response expectations.
  • Set governance expectations for unstructured data and retrieval across Claims (document ingestion, parsing/OCR, layout-aware extraction, metadata/lineage, access controls, PII detection/redaction, auditability), including embedding/retrieval strategies and grounding validation aligned to enterprise standards.
  • Accountable for AI governance and compliance-by-design across the Claims portfolio, partnering with Legal, Compliance, Model Risk, Privacy, Security, and Audit; maintain audit readiness with clear controls, artifacts, escalation paths, and operational evidence.
  • Influence technology integration and platform strategy by partnering with Technology, Data, AI Platform, AI/MLOps, and Architecture teams on tooling, standard work, reusable capabilities, and scalable patterns for Predictive, Generative, and Agentic AI.
  • Champion reuse and scalability by partnering with AI platform owners and peers to develop and integrate reusable Claims AI capabilities within The Hartford's AI platform.
  • Provide thought leadership and change leadership: educate stakeholders, identify new AI opportunities, advance a data-driven culture, and drive change to core Claims processes through innovative quantitative/AI techniques.
  • Oversee portfolio planning, dependencies, resourcing, and financial stewardship, adapting to changing priorities, capacity constraints, technical risks, and regulatory needs while driving continuous improvement in delivery effectiveness and value realization.
  • Maintain strong knowledge of business processes and data sources and stay current on advancements in Machine Learning, GenAI/agentic frameworks, evaluation/guardrails, MLOps, cloud engineering, and emerging technologies.

Skills & Leadership Capabilities
  • Demonstrated experience leading large, complex Applied AI portfolios in regulated enterprise environments with consistent delivery discipline and risk management.
  • Strong business partnership and influence skills-able to translate Claims objectives into AI product strategy/roadmaps and drive adoption through operating model alignment and stakeholder engagement.
  • Deep technical fluency across Predictive ML + Generative + Agentic AI, including prompt engineering, RAG, agentic frameworks, evaluation methods, guardrail management, and AI/MLOps/model lifecycle management.
  • Strong governance and responsible AI grounding: model risk management, fairness/safety, explainability, monitoring, and compliance-by-design.
  • Applied understanding of unstructured data and retrieval systems (document ingestion pipelines, OCR, layout-aware extraction, embeddings, hybrid/dense retrieval, reranking, metadata/lineage, PII controls).
  • Proven ability to build and grow high-performing technical teams and establish operating rhythms across multiple teams/value streams.
  • Exceptional communication skills-able to communicate effectively at all levels and convert complex technical trade-offs into clear business implications and decisions.
  • Strong strategic thinking, analytical capability, negotiation/influence, conflict resolution, and ability to work autonomously across multiple priorities.

Education & Experience
  • 12+ years of applicable experience in Data Science, Applied AI, Analytics, Machine Learning Engineering, or related fields, including building and scaling AI solutions in production.
  • 7+ years of formal people leadership experience (leading leaders and/or multi-team organizations.
  • Insurance and/or Claims domain experience strongly preferred, with demonstrated success driving AI-enabled process transformation.
  • Bachelor's degree required; Master's or Ph.D. preferred in Machine Learning, Data Science, Computer Science, Applied Mathematics, or similar analytical field.
  • Proficiency with cloud platforms (preferably AWS or GCP) and their AI/ML ecosystems.

Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$182,400 - $273,600
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It's Like to Work Here | Perks & Benefits

What The Hartford employees say

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About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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