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Founding Machine Learning Engineer Jobs in Philadelphia, PA

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Founding Machine Learning Engineer information

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$31.8K

$129.9K

$195.3K

How much do founding machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for founding machine learning engineer in Philadelphia, PA is $129,939.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $156,400.00 per year, depending on experience, location, and employer.

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $120,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses are also common components of compensation, especially in startup environments where they play a significant role in total earnings.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What are the key skills and qualifications needed to thrive as a founding machine learning engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.
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Founding Machine Learning Engineer jobs near you

Machine Learning Engineer, Specialist

Vangard, Inc.

Malvern, PA • On-site

Full-time

Re-posted 13 days ago

Job description

Supports and performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment.

Core Responsibilities

  • Leverages data pipeline designs and supports the development of data pipelines to support model development. Proficient with software tools that develop data pipelines in a distributed computing environment (PySprak, GlueETL).

  • Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production.

  • Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.

  • Supports data discovery & automated ingestion for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs.

  • Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.

  • Runs model monitoring scripts, follows process for alerts to management as needed. Addresses issues found in data pipelines from model monitoring alerts.

  • Participates in special projects and performs other duties as assigned.

Qualifications

  • Undergraduate degree or equivalent experience; a graduate degree is preferred.

  • Minimum of 5 years of relevant work experience.

  • At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).

  • Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.

  • Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.

  • Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.

  • Experience with API design and development is a plus.

  • Solid understanding of software engineering principles, including design patterns, testing, security, and version control.

  • Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.

  • Understanding of solution architecture for building end-to-end machine learning data pipelines.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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