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Artificial Intelligence Machine Learning Engineer information

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$30.1K

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$184.9K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for artificial intelligence machine learning engineer in Philadelphia, PA is $123,068.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,000.00 and $148,100.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

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

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Philadelphia, PA?

For Artificial Intelligence Machine Learning Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Philadelphia, PA look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Philadelphia, PA with the most Artificial Intelligence Machine Learning Engineer job openings:

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Philadelphia, PA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $123,068 per year, or $59.2 per hour.

Principal Data & Machine Learning Engineer

AKUVO LLC

Malvern, PA • On-site

$158K - $216K/yr

Full-time

Posted 26 days ago

Job description

THE OPPORTUNITY

AKUVO is seeking a Principal Data & Machine Learning Engineer to serve as the senior-most technical owner across AKUVO’s data platform, machine-learning models, and the services behind AKUVO IQ. This is a breadth role: you are equally at home building production applications and APIs, engineering the data lake and infrastructure, and developing and deploying predictive models — the person the team turns to at any layer.

You will lead the technical execution of the data and analytics strategy, own architecture across data engineering and machine learning, internalize critical systems currently held by external partners, and provide technical leadership and mentorship to the engineering team. The role combines hands-on engineering across the full stack with technical leadership and direct ownership of production systems.

LOCATION

Local in Malvern/Philadelphia first, widening to surrounding areas such as New Jersey, New York, Delaware, while continuing to expand geographically in a hybrid/remote capacity based on location.

KEY RESPONSIBILITIES

  • Lead the technical execution of the data and analytics strategy across data engineering and machine learning, and own the architecture for AKUVO’s data lake, ML platform, model pipelines, and the data services behind AKUVO IQ.
  • Work hands-on across the full stack — application and API development, systems and infrastructure, data pipelines, and predictive-model development — stepping directly into whichever layer the team needs.
  • Build, deploy, and maintain predictive models and scores alongside the Senior Data & Machine Learning Engineer, contributing directly to model development as well as the platform beneath it.
  • Internalize critical data and ML systems currently held by external partners through a structured knowledge-transfer and documentation process, building internal depth and reducing concentration risk.
  • Design scalable, reliable, and secure architectures for structured portfolio data, predictive-model data, and separately governed PII and AI-conversation data.
  • Own the operational disciplines for pipelines and production models — monitoring, alerting, incident response, versioning, drift detection, and retraining — so systems can be independently deployed, monitored, and enhanced.
  • Evolve technical practices for architecture, development, testing, CI/CD, observability, documentation, and data quality, and ensure data is accurate, timely, and traceable with clear lineage and governance.
  • Provide technical leadership, mentorship, and development to the engineering team, set technical direction, and coordinate delivery.
  • Partner with Applied AI, the Collections domain, Product, Engineering, Architecture & Innovation, and Compliance to keep data, models, and AI systems integrated, governed, and production-ready.
  • Evaluate technical investments, cost, and resource needs; make pragmatic build-versus-buy decisions; and document and prioritize key risks, dependencies, and technical debt.
  • Communicate architecture, risks, and priorities clearly to executive and cross-functional stakeholders, and advance AI-assisted engineering practices across the team.

SKILLS AND EXPERIENCE

  • 10+ years across software/data engineering and machine learning, with hands-on delivery spanning application development, systems and infrastructure, data platforms, and production ML models.
  • 3+ years providing technical leadership and developing engineers.
  • Full-stack breadth — able to build applications and APIs, engineer data pipelines and infrastructure, and develop, deploy, and maintain ML models; the person the team relies on at any layer.
  • Deep, hands-on experience with cloud data and ML platforms in production (Azure strongly preferred) — data lakes, layered architectures, pipelines, product-serving APIs, and model pipelines.
  • Strong Python and SQL, and modern engineering practices (ETL/ELT, CI/CD, observability, testing, environment management).
  • A track record of internalizing critical systems and knowledge through structured transitions, and of setting and evolving technical practices.
  • Ownership of the production model lifecycle — deployment, versioning, monitoring, drift detection, and retraining.
  • Proven ability to translate business and product priorities into scalable roadmaps and pragmatic build-versus-buy decisions.
  • Strong communication with executive, product, and cross-functional stakeholders, and comfort operating as a hands-on technical leader.
  • Active, sophisticated use of AI within your own engineering and leadership workflow.

PREFERRED QUALIFICATIONS

  • Experience spanning both software/platform engineering and applied ML in the same role — a rare full-stack-plus-modeling breadth.
  • Microsoft Fabric and OneLake, or experience leading a Synapse-to-Fabric migration; Databricks or comparable ML platforms.
  • B2B SaaS, fintech, or financial-services background (2+ years), ideally with collections, lending, or credit-scoring exposure.
  • Experience standing up or maturing model governance, documentation, and compliance practices.
  • Experience with sensitive, PII, or regulated data and separately governed data zones.
  • Azure DevOps and structured delivery processes (Epics → Features → Stories → Tasks).