Senior Machine Learning Engineer

Job Requisition ID #

Please read the following job description thoroughly to ensure you are the right fit for this role before applying.

24WD78709

Digital Experience & Customer Empowerment Machine Learning Team (DXC-ML)@Autodesk

The DXC-ML Team is responsible for delivering Machine Learning features that transform the customer experience for Sales, Marketing, and Customer Success functions at Autodesk.

We aim to help our customers, through conversation, personalization, and other intelligent features on our platform. Our team members work extensively with stakeholders across the company, with significant technology leadership and opportunity for impact.

We work in a supportive and collaborative way, applying the latest technology and rigorous analysis to solve complex customer problems using ML.

Position Overview

Our focus is on optimizing e-commerce through advanced techniques in conversion, segmentation, and behavior targeting. This initiative aims to enhance customer experiences and drive better business outcomes.

For instance, we are developing sophisticated models to personalize customer journeys, segmenting users based on behavior patterns, and implementing targeted marketing strategies.

Other examples of our work include creating algorithms to predict customer purchasing behavior, designing dynamic content for personalized shopping experiences, and measuring the impact of these optimizations on overall sales and customer satisfaction.

As a Senior ML Engineer of e-commerce on the team, you will be responsible for the design, analysis, and delivery of data-driven solutions to significant business challenges across a program of work.

Reporting to the Director of E-commerce ML, this role is hands-on, focusing on advanced technical skills with the latest in NLP and ML technology.

Our team culture is built on collaboration, mutual support, and continuous learning.

As a group, we continuously strive to improve our Machine Learning practices and stay abreast of trends and techniques relevant to our areas.

Our team is committed to excellence in both the theory and practice of Machine Learning, and we encourage personal development and knowledge sharing among all team members.

Job Location : San Francisco

Responsibilities

• Oversee the design and development of advanced ML models and algorithms to solve significant e-commerce optimization challenges, focusing on conversion, segmentation, and behavior targeting.
• Apply state-of-the-art ML technologies to create data-driven solutions that enhance customer experiences and drive business outcomes.
• Coordinate with multi-disciplinary stakeholder teams to ensure seamless delivery of ML-driven solutions, aligning technical efforts with business goals.
• Oversee the end-to-end lifecycle of ML projects, from initial data analysis and model development to deployment and performance monitoring.
• Provide technical guidance and mentorship to junior engineers, fostering a culture of continuous learning and mutual support within the team.
• Emphasize and implement agile, hands-on approaches in project execution, ensuring flexibility and responsiveness to evolving business needs.
• Stay up to date of the latest trends and techniques in Machine Learning, driving the continuous improvement of our ML practices and ensuring the team remains at the cutting edge of the field.
• Communicate complex technical concepts and project progress effectively to both technical and non-technical stakeholders, ensuring transparency and alignment.
• Implement robust testing and validation frameworks to ensure the accuracy, reliability, and scalability of ML models in production.
• Encourage and contribute to the team's knowledge sharing, fostering an environment that values innovative thinking and the exploration of new ideas in Machine Learning.

Minimum Qualifications

• 6+ years of relevant experience.
• Deep understanding of e-commerce and digital marketing principles, including customer segmentation, user behavior analysis, and conversion optimization.
• Strong focus on delivering measurable results and value to the business, with a data-driven approach to decision-making.
• Proficiency in SQL and experience with big data technologies such as Hive, Presto, Glue, (Py)Spark, or Athena.
• Advanced software engineering skills, including a strong understanding of data structures and algorithms.
• Experience with data pipelines and model serving in AWS, including MLOps practices, especially at scale.
• Strong background in designing and conducting experiments, including A / B testing, to validate ML models and strategies.
• Experience with causal inference methods to understand and model the effects of various interventions in e-commerce settings.
• Proficiency in developing and implementing models for behavior targeting to enhance personalized customer experiences and increase conversion rates.
• Knowledge of attribution modeling to accurately assess the impact of various marketing and optimization efforts.

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