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Hewlett Packard Enterprise

Builds servers, networking and private cloud

AI Engineer Lead

Applied Machine LearningPosted on Nov 13
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative discipline is required.
  • Typically, 7–10 years of experience is required.
  • Knowledge of NVIDIA AI Enterprise tools such as NeMo and NIM is required.
  • A deep understanding of machine learning algorithms, including linear regression, decision trees, support vector machines, random forests, neural networks, and reinforcement learning, is required.
  • Proficiency in model selection, hyperparameter tuning, and evaluating model performance with appropriate metrics is required.
  • A strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts, is required.
  • Proficiency in Python, R, or Java and experience developing production-level code are required.
  • Familiarity with software engineering best practices, version control systems such as Git, and software development methodologies is required.
  • Advanced knowledge and experience in deep learning, including neural network architectures such as convolutional neural networks, recurrent neural networks, and transformers, is required.
  • Knowledge of advanced techniques such as transfer learning, generative models, and optimization algorithms for deep learning is required.
  • Researching AI and machine learning advancements, exploring emerging technologies, and identifying opportunities to apply state-of-the-art techniques is required.
  • Strong problem-solving and critical-thinking abilities are required.
  • Strong programming skills in Python, R, or Java and experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn are required.

Responsibilities

  • Set up an AI agent workflow framework.
  • Research and stay current with advancements in AI and machine learning technologies, frameworks, and algorithms; explore and experiment with techniques to solve complex problems and improve models.
  • Collaborate with cross-functional teams to understand business requirements and design AI and machine learning solutions; select appropriate algorithms, models, and frameworks, and architect scalable, efficient, and robust systems.
  • Develop, implement, and optimize machine learning models and algorithms, including data preprocessing, feature engineering, model selection, hyperparameter tuning, and training on large datasets; monitor and improve model performance and accuracy.
  • Deploy machine learning models into production environments, accounting for scalability, performance, and security.
  • Integrate models with existing software systems and infrastructure to ensure reliable operation and interoperability.
  • Monitor deployed models, collect metrics, and analyze data to identify improvements; fine-tune models, optimize algorithms, and enhance system performance.
  • Organize and lead design review sessions, aligning discussions with project requirements and best practices; mentor and provide feedback to junior and mid-level team members.
  • Work with the engineering manager and team lead to set design and implementation standards and support continuous improvement and alignment with project goals.
  • Lead meetings to foster a collaborative and productive team environment.
  • Provide technical leadership, mentorship, and guidance to junior team members.
  • Proactively address and resolve challenges.
  • Develop and deliver strategic presentations and reports to senior stakeholders, providing technical and business insights and recommendations.
  • Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets.

Desired Qualifications

  • Knowledge of statistical modeling, data mining, and data visualization is highly preferred.
  • Knowledge of libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras is a plus.

About the Company

Hewlett Packard Enterprise

Builds servers, networking and private cloud

Hewlett Packard Enterprise sells servers, storage, networking and hybrid cloud software to large companies, governments and service providers. Its GreenLake platform lets customers run on-premises hardware as a metered cloud service, and its Cray supercomputers run national lab and AI training workloads. The networking business, built on Aruba and Juniper Networks, supplies campus, data-center and routing equipment. Revenue comes from hardware sales, multiyear support contracts, financing and subscriptions. The company traces its roots to Hewlett-Packard, founded in 1939, became a separate public company in 2015 and is headquartered in Houston, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1939

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