Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Senior - Tampa

Location: Tampa

At EY, we’re all in to shape your future with confidence. 

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.  Join EY and help to build a better working world.

Senior Machine Learning Engineer

EY is the only professional services firm with a separate business unit (“FSO”) that is dedicated to the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry. This practice also has several Service Delivery Centers that are made up of high-performing US-based resources who work closely with our experienced client-serving professionals to deliver project-based work and managed services to our US-based Financial Services clients. If you have a passion for rallying together to solve the most complex challenges in the financial services industry, come join our dynamic FSO team! 

The opportunity

Data has yet to be utilized to its fullest potential. Financial institutions are looking to build smarter and more efficient ways to operate their business, through new opportunities uncovered by their data. You’ll be solving complex problems, as well as giving deliverables to our clients in the AI and data space. With support from a highly talented team, you’ll have tremendous growth opportunities, with a focus on continuous learning and skills development to become a leader that can make significant contributions to companies.

Your key responsibilities

Candidate should possess deep hands-on expertise in designing, building, and deploying scalable machine learning systems, including advanced NLP and Generative AI (LLM) solutions. This position demands strong technical leadership, a quick learning ability, a proven track record in delivering high-value, production-grade AI solutions, and the capacity to mentor junior engineers.

Key Responsibilities

• ML System Design & Architecture: Lead the design and architecture of robust, scalable, and high-performance machine learning systems, ensuring seamless integration with existing platforms.
• Production ML Model Deployment: Own the end-to-end lifecycle of deploying and operationalizing machine learning models in production environments, ensuring efficiency, reliability, and maintainability.
• Advanced AI/ML Engineering: Develop, optimize, and implement advanced machine learning algorithms and statistical models, focusing on engineering best practices for performance and scalability.
• Generative AI & NLP System Development: Engineer and integrate cutting-edge Generative AI (LLM) and Natural Language Processing (NLP) solutions. This includes designing efficient prompting strategies, developing LLM-based data augmentation techniques, and implementing Retrieval-Augmented Generation (RAG, including advanced RAG) to enhance model capabilities within production systems.
• Deep Learning Infrastructure: Design and build systems to effectively apply and deploy deep learning techniques (ANN, LSTM, CNN, BERT, XLNet, Transformers, neural & LLM-based embeddings) for state-of-the-art AI applications at scale.
• MLOps & Automation: Establish and implement MLOps practices, including CI/CD pipelines, automated testing, monitoring, and retraining strategies for ML models to ensure continuous improvement and stability.
• Performance Optimization: Optimize ML models and underlying infrastructure for computational efficiency, speed, and resource utilization.
• Technical Leadership & Mentorship: Drive technical excellence, promote best coding practices, perform code reviews, and provide mentorship to junior engineers.
• Cross-Functional Collaboration: Partner closely with data scientists, product managers, and other engineering teams to translate complex business requirements into technical ML solutions and ensure successful delivery.
• Risk Management & Compliance: Integrate risk assessment and compliance considerations into ML system design and deployment, ensuring adherence to applicable laws, regulations, and internal policies to safeguard the firm's reputation and assets.

Qualifications

• Experience:
• 8+ years of hands-on experience in Machine Learning Engineering, MLOps, or AI system development.
• Minimum of 2 years of direct experience in engineering and deploying Generative AI/LLM solutions in production.
• Technical Skills:
• Deep proficiency in Python for production-grade ML development, with expertise in relevant libraries (scikit-learn, pandas, SpaCy, TensorFlow, PyTorch, Hugging Face Transformers).
• Strong experience with PySpark for large-scale data processing and building robust data pipelines.
• Proficiency in big data frameworks (Hadoop, Spark, Hive, Hue) and experience with streaming technologies.
• Extensive experience with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Airflow, CI/CD for ML).
• Proven experience in designing, implementing, and deploying NLP and deep learning models to production.
• Hands-on experience with Generative AI development, including engineering prompting strategies, RAG implementation, and LLM fine-tuning and integration (e.g., Langchain, LlamaIndex).
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Good to have: Experience with graph neural networks, graph databases, or distributed systems for ML.
• System Design & Architecture: Demonstrated ability to design scalable, fault-tolerant, and performant ML systems.
• Problem-Solving: Exceptional analytical, interpretive, and problem-solving skills with a focus on engineering challenges and innovative solutions.
• Communication: Excellent interpersonal, verbal, and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Autonomy & Leadership: Proven ability to work independently, drive projects to completion, and provide technical leadership and mentorship.

What we look for

We’re interested in professionals that are passionate about technology, who already have an understanding of data and are comfortable analyzing or manipulating it while generating reports for clients. You’ll also need to be able to clearly articulate both problems and proposed solutions, and have the willingness to learn and quickly adapt to changing requirements. On top of this, we’re looking for team players and hard workers who are not afraid to take initiative to master their craft and produce high-quality work. If you have a proactive approach and want to be part of a group that continues to grow significantly, this role is for you.

What working at EY offers

We offer a competitive compensation package where you’ll be rewarded based on your performance and recognized for the value you bring to our business. In addition, our Total Rewards package includes medical and dental coverage, both pension and 401(k) plans, a minimum of 15 days of vacation plus ten observed holidays and three paid personal days, and a range of programs and benefits designed to support your physical, financial, and social well-being. Plus, we offer:

• Opportunities to develop new skills and progress your career
• Support and coaching from some of the most engaging and knowledgeable colleagues
• A collaborative environment where everyone works together to create a better working world
• Excellent training and development prospects

About EY

As a global leader in assurance, tax, transaction, and advisory services, we hire and develop the most passionate people in their field to help build a better working world. This starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. So that whenever you join, however long you stay, the exceptional EY experience lasts a lifetime.

Join us in building a better working world. Apply now.

What we offer you
At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn  more .

• We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business.  The base salary range for this job in all geographic locations in the US is $65,500 to $134,000.  The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $78,600 to $152,100.  Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.  In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
• Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
• Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.

Are you ready to shape your future with confidence? Apply today. 
EY accepts applications for this position on an on-going basis.

For those living in California, please click here for additional information.

EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY  |  Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

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