Senior Advisor, Machine Learning

As a Machine Learning Engineer with a strong foundation in Data Science, MLOps, and Generative AI, you'll play a pivotal role in designing, developing, and deploying intelligent, scalable applications. You'll work across the stack—from front-end interfaces to back-end services and ML pipelines—bringing innovative, AI-driven solutions to life. You'll also contribute to the fine-tuning and operationalization of Large Language Models (LLMs) and other GenAI technologies to solve real-world business problems.

Join us as a
Senior Advisor
on our
Machine Learning
team in
Bangalore
to do the best work of your career and make a profound social impact.

What You'll Achieve
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.

You will:

• Build and maintain full-stack applications that integrate advanced ML models and real-time data pipelines.
• Collaborate with data scientists to fine-tune and productionize LLMs and other GenAI models using MLOps best practices.
• Design and implement scalable APIs and microservices to support AI/ML workloads.
• Design and implement observability frameworks for ML pipelines and production systems using tools such as Grafana, Splunk, Dynatrace, Catchpoint, and Lanfuse to monitor performance, latency, and reliability.
• Develop automated testing, monitoring, and alerting mechanisms to proactively detect anomalies, model drift, and system failures, leveraging dashboards, logs, and synthetic monitoring for real-time insights.
• Collaborate with business, engineering and data science teams to define KPIs, configure alert thresholds, and integrate observability and alerting into CI/CD workflows for continuous health checks and compliance

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

• 8+ years of experience in full-stack development with hands-on experience in  MLOps tools like MLflow, Kubeflow, or SageMaker and strong knowledge test end to end pipelines developed for model deployment and tools required for testing.
• Solid understanding of machine learning concepts, model lifecycle, and deployment strategies. and experience with cloud platforms (AWS, Azure, GCP) and container orchestration using Docker and Kubernetes.
• Experience in fine-tuning and deploying LLMs (e.g., GPT, LLaMA, Falcon) for domain-specific use cases and working knowledge of Grafana, Splunk, Dynatrace, Catchpoint, and Langfuse.
• Strong knowledge of RESTful APIs, microservices architecture, and SQL/NoSQL databases.

Desired Requirements

• Experience with Generative AI frameworks (e.g., LangChain, Hugging Face Transformers, OpenAI APIs).
• Familiarity with data streaming technologies like Apache Kafka or Spark Streaming and Exposure to big data ecosystems (Hadoop, Hive, etc.).

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: 20th Nov
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.

Job ID:
R280869