Manager, Machine Learning Engineering
41 Minutes ago • 8 Years +
Research Development
Job Description
This role seeks a Tech Lead Manager (TLM) with strong hands-on machine learning expertise to lead the development of scalable ML platforms and AI-driven automation agents. The TLM will balance technical leadership, team management, and project execution, guiding engineers and data scientists to deliver impactful solutions for global fraud detection. Responsibilities include defining technical strategy, architecture, mentoring, and contributing code. This role is key in shaping PayPal’s fraud detection agentic AI and ML, accelerating innovation across the data science community.
Good To Have:
- 6+ years of experience in ML/AI engineering or applied science.
- 1+ years in a tech lead or manager role driving projects to completion.
- Advanced degree (Master’s or PhD) in Computer Science, Engineering, or related field (or equivalent experience).
Must Have:
- Lead the development and optimization of advanced machine learning models.
- Oversee preprocessing and analysis of large datasets.
- Deploy and maintain ML solutions in production environments.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models, making necessary adjustments.
- Minimum of 8 years of relevant work experience.
- Bachelor's degree or equivalent experience.
- Proven ability to lead teams while staying hands-on in coding, design, and technical problem-solving.
- Strong background in machine learning frameworks (e.g., PyTorch, TensorFlow, XGBoost, scikit-learn).
- Experience with agent frameworks and LLM-based systems (e.g., ReAct, AutoGPT, HuggingGPT, RAG).
- Skilled in Python and building production-quality systems using software engineering best practices.
- Excellent project execution and delivery skills.
- Strong communication and collaboration skills.
Perks:
- Flexible work environment (hybrid model)
- Employee shares options
- Health insurance
- Life insurance
Job Summary:
We are looking for a Tech Lead Manager (TLM) with strong hands-on machine learning expertise to lead the development of scalable ML platforms and AI-driven automation agents. In this role, you will balance technical leadership, team management, and project execution, guiding engineers and data scientists to deliver impactful solutions for fraud detection at global scale.
As a TLM, you will drive execution end-to-end: from defining technical strategy and architecture, to mentoring team members, to contributing code and prototypes yourself. You’ll play a key role in shaping PayPal’s fraud detection agentic AI and ML, enabling hundreds of use cases and accelerating innovation across our data science community.
Job Description:
Essential Responsibilities:
- Lead the development and optimization of advanced machine learning models.
- Oversee the preprocessing and analysis of large datasets.
- Deploy and maintain ML solutions in production environments.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models, making necessary adjustments.
Minimum Qualifications:
- Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience.
Preferred Qualification:
About You
- 6+ years of experience in ML/AI engineering or applied science, with 1+ years in a tech lead or manager role driving projects to completion.
- Proven ability to lead teams while staying hands-on in coding, design, and technical problem-solving.
- Strong background in machine learning frameworks (e.g., PyTorch, TensorFlow, XGBoost, scikit-learn).
- Experience with agent frameworks and LLM-based systems (e.g., ReAct, AutoGPT, HuggingGPT, RAG), including evaluation and optimization.
- Skilled in Python and building production-quality systems using software engineering best practices.
- Excellent project execution and delivery skills — able to set direction, manage priorities, and keep teams on track.
- Strong communication and collaboration skills, with experience influencing cross-functional partners.
- Advanced degree (Master’s or PhD) in Computer Science, Engineering, or related field (or equivalent experience).
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