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Executive Full Stack Machine Learning Engineer Jobs in Pennsylvania

Machine Learning Engineer - Autonomy Lab

Pittsburgh, PA · On-site

$99K - $131K/yr

As a machine learning engineer in the AI for Autonomy Lab, you willidentify, shape, apply, conduct ... Applied Full-Stack Implementation: You have strong development experience and can design and ...

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Executive Full Stack Machine Learning Engineer information

Will AI replace full-stack dev?

As an Executive Full Stack Machine Learning Engineer, it is unlikely that AI will fully replace full-stack developers, as their roles require complex problem-solving, creativity, and understanding of business needs that AI cannot replicate. AI tools can automate certain coding tasks and improve efficiency, but human oversight and expertise remain essential for designing, integrating, and maintaining full-stack applications. The evolving landscape emphasizes collaboration between AI and developers rather than replacement.

What engineer makes $500,000 a year?

An executive full stack machine learning engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in AI and software development, and working at large tech companies or startups with competitive compensation packages. High salaries often include base pay, bonuses, and stock options, reflecting seniority and expertise in the field.

Will MLE be replaced by AI?

An Executive Full Stack Machine Learning Engineer designs and implements AI systems, but AI is a tool that complements rather than replaces such roles. While automation and AI advancements can handle certain tasks, skilled engineers are needed for developing, maintaining, and improving complex machine learning solutions. Continuous learning and expertise in programming, data analysis, and model deployment remain essential in this field.

What is the salary of full-stack machine learning engineer?

The salary of a full-stack machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those requiring specialized skills in deep learning or cloud platforms may offer higher compensation.

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

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Pennsylvania? The most popular types of Full Stack Machine Learning Engineer jobs in Pennsylvania are:
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Full-Stack Engineer

$110K - $160K/yr

Full-time, Part-time

Medical, Life, Retirement, PTO

Re-posted 10 days ago


Job description

SALARY RANGE: $110,000 - $160,000 per year

In determining compensation, various factors will be considered, including but not limited to, educational background; relevant experience, knowledge, skills, and abilities, market factors; and geographic location.

BENEFITS: All eligible full time employees will receive Paid Annual Leave (PAL) starting at 23 days per year and raising by one day per year following one full calendar year of employment (January through December). They will also be offered health benefits and will be automatically enrolled in employer paid short and long term disability and life insurance.

All full time and part time employees have access to participate in the Delphinus Engineering 401(k) which includes company match of 25% up to 10% deferred.

GENERAL SUMMARY: The Full-Stack Engineer position is instrumental in designing, developing, and maintaining sophisticated Condition Assessment Systems that are crucial for naval operations. The Full-Stack Engineer will leverage a modern tech stack centered on GoLang, Kubernetes, and event-driven microservices to build resilient, scalable platforms that directly impact naval readiness and maintenance strategies.

LOCATION: Philadelphia, PA

PRINCIPAL DUTIES/RESPONSIBILITIES:

  • Design, build, and enhance event-driven microservices and software utilities using GoLang, with exposure to Javascript and Kotlin.
  • Develop critical software upgrades and enhancements for advanced Condition Assessment and Remote Monitoring systems.
  • Own the CI/CD pipeline using GitLab CI, Ansible, and Terraform to automate builds, testing, and deployments in a Kubernetes environment.
  • Provide RDBMS support for PostgreSQL and time-series databases (e.g., InfluxDB, TimescaleDB), including schema design, optimization, and administration.
  • Implement and manage robust monitoring and observability solutions using Prometheus and Grafana to ensure system health and performance.
  • Provide engineering services to gather, validate, and analyze shipboard data, troubleshooting issues and supporting the development of equipment logistic models.
  • Conduct hardware setup, maintenance, and rigorous software development testing in accordance with IEEE standards.

EDUCATION AND EXPERIENCE REQUIREMENTS:

  • Bachelor’s level degree in Computer, Electrical or Electronics Engineering, or Mathematics with field of concentration in computer science or equivalent. from an accredited college or university.
  • At least 5 years of experience in computer design, software development or computer networks including Linux, Kubernetes, RabbitMQ, Vue, GIT.
  • At least 5 years of experience in Database Development, Web Development or application development using real-time data acquisition and analysis, batch data processing, data storage and retrieval, and user interface applications.
  • Experience in the design, development, and implementation of machinery lifecycle management software systems preferred.
  • Familiarity with and have developed applications using the DoDAF standards preferred.

SPECIAL REQUIREMENTS:

  • Successful applicants must either have an active government security clearance or the ability to receive approval upon position acceptance.
  • Must have a valid US passport or the ability to obtain one upon position acceptance.
  • Ability to obtain OS certification or complete approved related training within 180 days of hire.
  • A+ CE, CCNA-Security, CND, Network+ CE, or SSCP certification preferred.
  • U.S. Citizenship is required.

SKILLS AND ABILITIES:

Essential Skills:

  • Proven experience developing robust backend services using GoLang (10+ years preferred).
  • Expertise in designing and building event-driven microservices architectures (10+ years preferred).
  • Deep understanding and hands-on experience with container orchestration using Kubernetes (7+ years preferred).
  • Experience with message brokers such as RabbitMQ, Kafka, or NATS (7+ years preferred).
  • Proficiency with API design and implementation using gRPC and GraphQL (7+ years preferred).
  • Strong DevOps mindset with hands-on experience in GitLab CI, Ansible, and Terraform (5+ years preferred).
  • Solid experience with observability tools like Prometheus and Grafana (7+ years preferred).
  • Expert-level proficiency with Git for version control.
  • Strong command of Linux environments.
  • Advanced SQL skills and experience with relational databases (e.g., PostgreSQL, MS SQL, etc.) (10+ years preferred).
  • Experience with time-series databases (e.g, TimescaleDB, InfluxDB, etc.) (7+ years preferred).

Additional Preferred Skills:

  • Experience in industrial analytics, machinery diagnostics, or condition-based maintenance (CBM) systems.
  • Prior experience delivering Data-as-a-Service (DaaS) or Platform-as-a-Service (PaaS) solutions.
  • Familiarity with U.S. Government or Department of Defense development environments.