NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Machine Learning Engineer to join our team remotely in the United States.

How You’ll Help Us: 

As an NTT DATA Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and systems at scale. You'll implement machine learning applications using existing and emerging technology platforms to deliver business value to NTT DATA's clients.

You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You’ll also mentor other engineers and develop your technical knowledge and skills to keep NTT DATA at the cutting edge of technology. 

How We Will Help You: 

Joining our ML/AI practice is not only a job, but a chance to grow your career. We will make sure to equip you with the skills you need to produce robust applications that you can be proud of. Whether it is providing you with training in a new programming language or helping you get certified in a new technology, we will help you grow your skills so you can continue to deliver increasingly valuable work. 

Why the Role Is Important: 

Developers are the core of everything we create, and your work is instrumental in our success. We strive to be the first firm companies think of when it comes to fulfilling their technology needs, and our best evidence is the successful solutions created by our developers. Finally, you will use the experience you have and the experience you will gain to help less experienced developers succeed in their roles. 

Once You Are Here, You Will: 

• Focus on ML system iteration and performance measurement 

• Iterate on existing ML models built for high-impact game recommendation and personalization applications, by benchmarking and adding new features to the model, tuning the blending of multiple models’ predictions, and enhancing model inference efficiency  

• Iterate on existing offline and online evaluation metrics, and study the correlations between metrics 

• Evaluate model performance by running suites of metrics in offline evaluation, as well as using online experiment data, and performing subgroup analysis, to help the team find the next improvement area that will gain maximum KPI lift 

• Enhance the explainability of models running in production, providing additional insights for our product and business partners to better use our models and make a better roadmap 

• Collaborate with existing machine learning engineers and data scientists and backend engineers from cross-functional teams 

Basic Qualifications: 

• 3+ years of experience working in ML/DS teams (pls don’t include years in a research group or R&D team) 

• 5+ years of experience with programming Python/Scala 

• 5+ years of experience with machine learning libraries and frameworks like TensorFlow, PySpark. 

• 1+ years of experience in Databricks, mlFlow, Seldon 

Preferred Qualifications: 

• Proven track record of successfully delivering large-scale commercial machine-learning products from conception to production 

• Excellent problem-solving skills and analytical skills 

• Expertise in recommendation algorithms 

• Experience with software engineering principles, and use of cloud services like AWS 

• Experience in Snowflake, Kubeflow, Tecton, Jenkins 

• Experience analyzing large-scale data and delivering insights 

• Experience in building large-scale online customer-facing ML applications, preferably recommendation systems 

• Experience working with custom ML platforms, feature store, and monitoring ML models 

• Familiarity with best practices in machine learning, A/B test analysis and casual inference

• Advanced degree (Master’s or Ph.D.) in Computer Science/Statistics/Data Science, specializing in machine learning