Job Overview

HP is hiring an AI Solutions Engineer in Bengaluru for a full-time software role focused on machine learning model development, deployment, and lifecycle management. This position is suited to an experienced AI and machine learning professional who can turn algorithms and statistical methods into production-ready solutions that support business or research needs.

The role covers the full machine learning lifecycle, from designing experiments and training models to validation, optimization, production deployment, monitoring, and maintenance. The selected engineer will work closely with research, engineering, and CI/CD teams to build scalable ML pipelines and help improve automated model training practices.

Key Responsibilities

• Develop software solutions that support the development, deployment, and ongoing lifecycle of machine learning models.
• Train and validate machine learning models using suitable evaluation methods and performance metrics.
• Experiment with ML algorithms and tune hyperparameters to improve model quality and generalization.
• Design and maintain machine learning pipelines capable of producing scalable models efficiently.
• Deploy trained models into production while considering scalability, reliability, and operational efficiency.
• Monitor deployed models and make updates when data, requirements, or model behavior changes.
• Design ML systems and conduct experiments to identify effective approaches for business or research problems.
• Work with CI/CD teams to integrate model delivery into production deployment processes.
• Collaborate with research and engineering teams to improve automated training and model lifecycle practices.
• Apply machine learning and statistical modeling techniques to practical problems.
• Contribute to testing and maintenance activities throughout the model lifecycle.

Required Skills

Candidates should have strong practical knowledge of machine learning, algorithms, statistical methods, and software engineering. The role requires the ability to develop and evaluate models, understand model performance, optimize configurations, and support production deployment.

Python is an important programming language for this position, while the job description also identifies Java and C++ as relevant programming skills. Candidates should understand machine learning workflows and be comfortable working with modern ML libraries and frameworks.

Experience with PyTorch, TensorFlow, and Scikit-learn is relevant to the role. Knowledge of Apache Spark and big data concepts is also valuable for building solutions that can process and train against larger datasets.

Preferred Skills

The job description lists AWS Certified Machine Learning Specialty as the preferred certification. Experience with cloud environments, particularly Amazon Web Services and Microsoft Azure, can support the responsibilities associated with deploying and maintaining machine learning solutions.

Knowledge of deep learning, natural language processing, artificial intelligence, automation, and data science is also relevant. Candidates who can combine machine learning expertise with strong software engineering practices will be well aligned with the position.

Education

A four-year or graduate degree in Computer Science, Statistics, Mathematics, Data Science, or a related discipline is recommended. Equivalent work experience or demonstrated competence may also be considered according to the job description.

Experience

The typical requirement is 4 to 7 years of professional experience in areas such as computer programming, machine learning, algorithms, statistical methods, or related fields. Candidates with an advanced degree may qualify with 3 to 5 years of work experience.

This is an experienced AI engineering opportunity rather than a fresher role. Applicants should be able to demonstrate practical experience building, testing, optimizing, deploying, or maintaining machine learning solutions.

Required Technologies

Relevant technologies and technical areas identified in the job description include Python, Java, C++, Machine Learning, Artificial Intelligence, Deep Learning, Natural Language Processing, Apache Spark, PyTorch, TensorFlow, Scikit-learn, Amazon Web Services, Microsoft Azure, Big Data, Statistical Modeling, Algorithms, Software Engineering, and CI/CD.

Soft Skills

The role requires effective communication, results orientation, learning agility, digital fluency, and customer centricity. Strong collaboration is important because the engineer will work with research, engineering, and CI/CD teams.

The position may also provide direction to team activities and facilitate information validation and decision making. Candidates should therefore be comfortable explaining technical concepts, learning new technologies, and contributing to team-level outcomes.

Benefits of Working in this Role

This opportunity provides exposure to the complete machine learning lifecycle, including experimentation, model training, validation, optimization, deployment, monitoring, and maintenance. Engineers can work across machine learning, software engineering, cloud technologies, big data, and automation while contributing to solutions designed for practical business or research problems.

Work Mode

The provided job description does not explicitly state onsite, hybrid, or remote work mode. The position is based in Bengaluru, Karnataka, India, and is listed as a full-time role.

Location

The role is located in Bengaluru, Karnataka, India.

Who Should Apply

This opportunity is suitable for AI Solutions Engineers, Machine Learning Engineers, ML Software Engineers, Data Science professionals with strong engineering skills, and experienced software professionals who have built production-oriented machine learning solutions.

Applicants should highlight their hands-on work with model development, validation, hyperparameter optimization, ML pipelines, production deployment, monitoring, and machine learning frameworks. Experience with Python, PyTorch, TensorFlow, Scikit-learn, Apache Spark, AWS, or Azure should be presented accurately where applicable.

Career Growth

The position can help experienced professionals deepen their expertise across machine learning engineering, production AI systems, cloud deployment, data science, automation, and software engineering. Continued development in model lifecycle management, scalable ML architecture, cloud technologies, and advanced AI techniques can support progression toward senior AI engineering, machine learning architecture, or technical leadership responsibilities.

Application Advice

When applying, focus your resume on measurable machine learning and software engineering work. Highlight projects involving model training, validation, optimization, deployment, monitoring, ML pipelines, or production integration. Mention the programming languages, frameworks, cloud platforms, and data technologies you have actually used.

If you hold the AWS Certified Machine Learning Specialty certification, include it clearly. Also describe your experience with deep learning, NLP, big data, or statistical modeling when relevant. Keep the application factual and demonstrate how your technical background matches the complete machine learning lifecycle described for this role.