ZipRecruiter

Log In

1

Director Google Machine Learning Engineer Jobs in Springfield, MA

Cigna

Data Science Director - Remote

Bloomfield, CT · On-site +1

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Provide technical leadership across machine learning, statistical modeling, feature engineering ...

New

Infosys

AI Engineer

Hartford, CT · On-site

The role of AI Engineer involves developing and operationalizing machine learning models, ensuring data quality, and collaborating with business and technology teams to create analytics solutions.

Pwc

NGA AI Engineer Senior Manager

Hartford, CT

$91K - $321K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Direct the team through complexity, demonstrating composure through ambiguous, challenging and ...

Pwc

CTIO AI Engineering Manager

Hartford, CT

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

next page

Showing results 1-20

All JobsGoogle Machine Learning Engineer JobsDirector Google Machine Learning Engineer JobsDirector Google Machine Learning Engineer Jobs in Springfield, MA

Director Google Machine Learning Engineer information

See Springfield, MA salary details

$35.9K

$91.6K

$140.5K

How much do director google machine learning engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for director google machine learning engineer in Springfield, MA is $91,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,200.00 and $105,600.00 per year, depending on experience, location, and employer.

Is L7 senior at Google?

At Google, L7 is considered a senior-level position, typically involving significant technical expertise and leadership responsibilities. It is often associated with senior engineers or managers, depending on the role and team structure.

What engineer makes $500,000 a year?

A senior Google Machine Learning Engineer or Director level in large tech companies can earn $500,000 or more annually, often including base salary, bonuses, and stock options. These roles typically require extensive experience, advanced skills in machine learning and AI, and often involve leadership responsibilities and high-impact projects.

How much does a Google Engineering director make?

A Google Engineering Director typically earns between $200,000 and $300,000 annually, with total compensation including bonuses and stock options often exceeding this range. Compensation varies based on experience, location, and performance, and senior roles may include additional benefits and incentives.

Will MLE be replaced by AI?

As a Google Machine Learning Engineer, the role involves developing and deploying AI models, but AI is a tool that enhances rather than replaces MLE work. MLEs focus on designing, optimizing, and maintaining machine learning systems, which require expertise in data science, programming, and domain knowledge that AI cannot fully replicate. The role is expected to evolve with advancements in AI, emphasizing collaboration with AI systems rather than replacement.
What are the most commonly searched types of Google Machine Learning Engineer jobs in Springfield, MA? The most popular types of Google Machine Learning Engineer jobs in Springfield, MA are:
What are popular job titles related to Director Google Machine Learning Engineer jobs in Springfield, MA? For Director Google Machine Learning Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Director Google Machine Learning Engineer jobs in Springfield, MA look for? The top searched job categories for Director Google Machine Learning Engineer jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Director Google Machine Learning Engineer jobs? Cities near Springfield, MA with the most Director Google Machine Learning Engineer job openings:
Director Google Machine Learning Engineer jobs near you

AI Architect in Hartfort, CT 06155 and Charlotte, NC 28212 - Hybrid

Amicis Global

Hartford, CT • On-site

$80 - $90/hr

Contractor

Posted 18 days ago

Job description

ob Title: AI Architect
Location:  Hartfort, CT 06155 - Hybrid
Duration: 06 Months + Extensions
 
Role Overview:
The Hartford is seeking a highly skilled, hands-on AI Architect to support the Enterprise Technology Architecture (ETA) organization. This role will be responsible for leading the design, governance, and implementation of AI-centric technology architectures across a hybrid infrastructure landscape, including AWS, Google Cloud Platform (GCP), and on premises data centers.
The AI Architect will play a critical role in enabling the responsible and secure adoption of Generative AI (GenAI) technologies, establishing architectural standards, and driving the implementation of multiple internal-facing GenAI use cases. This role requires a strong blend of strategic architectural background and hands-on technical execution.
Key Responsibilities:
Architecture & Strategy
  • Design and develop Agentic AI solutions leveraging Google ADK, LangGraph/Langchain  and Agent Engine on Google Cloud Platform (GCP).
  • Deliver innovative AI capabilities that enhance business processes and customer experiences through GenAI and Agentic AI frameworks.
  • Ensure AI solutions align with enterprise technology strategy and meet scalability, security, and compliance requirements.
  • Drive adoption of GenAI and Agentic AI frameworks across business units.
  • Conduct proof-of-concepts (POCs) for emerging AI technologies and frameworks.
  • Collaborate with enterprise architects to ensure AI solutions align with technology strategy and reference architectures.
  • Stay current with AI trends, frameworks, and best practices to propose innovative solutions.
  • Cloud Security (AWS & GCP)
  • Architect and implement secure cloud solutions leveraging native services and third-party tools.
  • Define and enforce cloud security posture management (CSPM), identity and access management (IAM), and encryption strategies.
  • Collaborate with DevOps and cloud engineering teams to embed security into CI/CD pipelines and infrastructure-as-code.
  • Datacenter & Hybrid Security
  • Ensure secure integration between cloud platforms and on-prem data centers, including network segmentation, VPNs, and secure data flows.
  • Oversee security controls for legacy systems and their modernization paths.
  • GenAI Security Enablement
  • Define security and governance frameworks for GenAI platforms and use cases.
  • Ensure responsible AI practices including data privacy, model integrity, and ethical AI usage.
  • Collaborate with AI/ML teams to secure model training, inference, and deployment pipelines.
  • Governance & Collaboration
  • Serve as a key member of the Enterprise Technology & Solution Governance
  • Partner with business, IT, and risk stakeholders to align security architecture with enterprise goals.
  • Provide technical guidance and mentorship to junior engineers and architects on AI development practices.
Required Qualifications:
Experience:
  • 10-12 years in Software Engineering, with at least 2+ years in GenAI and Agentic AI development.
  • Project Delivery:
  • Must have delivered at least one GenAI or Agentic AI project end-to-end.
Technical Expertise:
  • Strong proficiency in Google ADK, LangGraph/Langchain, Agent Engine, and Vertex AI.
  • Hands-on experience with GCP services: Cloud Run, ECS, Vertex AI Search Engine, IAM, and networking.
  • Solid understanding of GenAI patterns, LLM fine-tuning, and prompt engineering.
Programming Skills:
  • Python, Java, or similar languages for AI development.
Cloud Certifications:
  • GCP Professional Machine Learning Engineer or GCP Professional Cloud Architect preferred.
Education:
  • Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
Soft Skills:
  • Strong problem-solving, communication, and collaboration skills.

Key Competencies:
  • Strategic and analytical thinking
  • Successfully integrated AI agents into business or technical workflows for automation and enhanced decision-making.
  • Improved operational efficiency and customer experience through AI-driven innovation.
  • Established reusable AI patterns and best practices for enterprise adoption.
  • Strong communication and stakeholder engagement
  • Proactive and solution-oriented mindse 
 
 
#CareerBuilder #Monster #Dice #Indeed #LinkedIn