Machine Learning Engineer Senior Advisor At DELL

Dell’s Commitment:

Dell Technologies is devoted to the principle of the same employment possibility for all employees and to offering a piece of surroundings freed from discrimination and harassment. We believe in the energy of variety and inclusion and strive to create a place of job wherein all of us can thrive. You can look at extra approximately our Equal Employment Opportunity Policy properly here.

Role: Machine Learning Engineer Senior Advisor

Company: Dell Technologies

Experience: 3 – 8 years

Salary: Not Disclosed

Location: Bengaluru

Company Overview:

Dell Technologies is a global leader in business company and era services, using digital transformation through innovative solutions that help corporations modernize technology, optimize approaches, and enhance client testimonies. With a determination to foster an inclusive and collaborative artwork environment, Dell is dedicated to empowering people and groups to reap their entire ability. The corporation believes in creating a profound social impact through its artwork, shaping a future in which technology plays an important feature in enhancing the way we live, paint, and play.

Job Summary:

Dell Technologies is searching for a fantastically skilled AI/ML Engineer who specializes in LLMOps (Large Language Model Operations) to enroll in their Machine Learning Engineer Team. The function consists of deploying contemporary General/Generative AI solutions, making sure operational performance, scalability, and accountable use of those models. This feature gives the possibility to interact in progressive projects that leverage huge datasets and contemporary language fashions, the use of choice-making, and operational efficiencies throughout global systems.

Key Responsibilities:

Architecting and Scaling ML/LLM Models:

• Design and put into effect scalable system studying (ML) and big language models (LLM) for green deployment across numerous structures.
• Apply LLMOps super practices to optimize the deployment and operation of these models.

Data Pipeline Optimization:

• Build and beautify records pipelines to operationalize ML and LLM fashions at scale.
• Utilize advanced activation engineering strategies and set up LLM guardrails to ensure the fashion’s characteristics efficiently and responsibly.

Multi-Agent System Development:

• Develop and install LLM-primarily based multi-agent structures, ensuring seamless scalability and green verbal exchange among dealers.

Collaboration and Model Refinement:

• Work carefully with information scientists to refine algorithms and fashions based on performance metrics.
• Implement human feedback loops and reinforcement reading from human feedback (RLHF) methods to continually enhance the model’s overall performance.

API and SDK Development:

• Develop APIs, SDKs, and LLM chains/pipelines to permit seamless interplay with deployed fashions.
• Incorporate moral AI thoughts in all tendencies to ensure responsible and truthful use of AI technologies.

Infrastructure Management:

• Implement Docker boxes, orchestrate load balancing, and manipulate LLM-specific infrastructure.
• Optimize resource allocation and employ vector databases for inexperienced information managing, retrieval, and context control in LLM/RAG (Retrieval-Augmented Generation) programs.

Essential Requirements:

Educational Background: Master or Bachelor in an applicable field with 8+ years of revel in statistics technological information and ML/LLM model deployment.

Technical Expertise: Mastery of data technological expertise systems (Microsoft Azure, AWS, Google Cloud) for constructing and deploying ML and LLM models. Proficiency in LLMOps high-quality practices.

Programming Skills: Strong expertise in item-oriented programming languages and LLM-precise frameworks such as LangChain, LangGraph, and LlamaIndex. Experience in set-off engineering.

Software Engineering: Significant revel in software program engineering with a focal point on ML/LLM version manufacturing, scalability in low-latency environments, and accountable AI implementation.

Cloud and DevOps: Advanced statistics of Docker, Kubernetes, cloud-local computing, DevOps, information/LLM reaction streaming, and parallelized workloads for ML and LLM deployments.

Database Management: Knowledge of vector databases, LLM terrific-tuning techniques, and implementation of LLM guardrails. Experience in LLM operations, along with RAG, chatbot, and multi-agent gadget deployments (e.g., CrewAI, AutoGen, LangGraph).

Desirable Requirements:

Data Engineering: Experience in Data Engineering (Spark), Message Queues (RabbitMQ, Kafka), and programming languages like Python, SQL, C++, and R.

Database Optimization: Proficiency in databases (Postgres, MongoDB, SQL Server, Redis) and their optimization for ML/LLM workloads, which encompass vector databases for efficient context retrieval.

Benefits of Working at Dell Technologies:

Career Growth Opportunities: Dell offers big professional development applications, mentorship possibilities, and clear career development paths, permitting employees to advance their careers.

Work-Life Balance: Dell is aware of the significance of labor-life balance and offers bendy working preparations, properly being programs, and beneficiant paid time off to assist personnel’ properly being.

Competitive Compensation: Dell affords competitive revenue applications, bonuses, and blessings, making sure that employees are rewarded for their contributions and understanding.

Innovative Work Environment: Dell fosters a way of life of innovation, encouraging personnel to convey new ideas and solutions to the table. Working at Dell technique being at the vanguard of technological enhancements.

Global Impact: Dell’s artwork has an international impact, permitting employees to contribute to duties and obligations that make a distinction international. This experience of motive drives the employer’s challenge and values.

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