Consultant, Machine Learning Engineer
Round Rock, Texas, United States
Dell Technologies
Dell bietet Technologielösungen, Services und Support. Notebooks, Touchscreen-PCs, Desktop-PCs, Server, Speicher, Monitore, Gaming und Zubehör kaufenConsultant, Machine Learning Engineer
Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What’s more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.
Join us to do the best work of your career and make a profound social impact as a Consultant, Machine Learning Engineer on our Machine Learning Engineer Team in Austin, Texas.
What you’ll achieve
As a Senior Machine Learning Engineer, you will be integral to deploying sophisticated General AI solutions, ensuring their operational efficiency and scalability. Engage in innovative projects that leverage massive datasets to drive decision-making and operational efficiencies across global platforms.
You will:
- Architect and scale machine learning models for efficient deployment across various platforms.
- Build and optimize data pipelines to operationalize machine learning models at scale.
- Work collaboratively with data scientists to refine algorithms and models based on performance metrics like scale, latency, and throughput.
- Develop APIs and SDKs to enable seamless interaction with deployed machine learning models.
- Implement Docker containers and orchestrate load balancing to optimize resource allocation.
- Utilize vector databases for efficient data handling and retrieval.
Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:
Essential Requirements
- Mastery in data science platforms such as Domino Data Lab, Microsoft Azure, AWS, and Google Cloud for building and deploying models.
- Proficient in object-oriented programming languages like C# or Java, with solid experience in Python, Spark, TensorFlow, XGBoost.
- Significant software engineering experience with a focus on ML model production and scalability in low-latency environments.
- Expert in data mining, ETL, SQL OLAP, Teradata, and Hadoop.
- Advanced understanding of Docker, Kubernetes, cloud-native computing, DevOps, data streaming, and parallelized workloads as well as knowledge of load balancing and vector databases.
Desirable Requirements
- 12–15 years of professional experience in languages like C++, SQL, R, or Python with experience in Data engineering (Spark) , Message queue ( RabbitMQ, Kafka)
- Proficiency in databases ( Postgres, , Mongo Db, Redis, SQL server) and its optimization and extensive experience in machine learning, particularly in developing solutions utilizing Neural Networks.
- Profound knowledge in Big Data technologies and real-time analytics.
Who we are
We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.
Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.
Application closing date:15 JULY 2026
Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs AWS Azure Big Data Data Mining Data pipelines DevOps Docker Engineering ETL GCP Google Cloud Hadoop Java Kafka Kubernetes Machine Learning ML models OLAP OOP Pipelines PostgreSQL Python R RabbitMQ Spark SQL Statistics Streaming TensorFlow Teradata XGBoost
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