Senior AI Engineer

Company Description Altimetrik is an AI-native engineering company that builds systems to power modern enterprises through its AI engineering operating system, ALTi AIOS™, and a robust partner ecosystem that includes OpenAI, Google Cloud, Anthropic, Snowflake, and Databricks. The company helps organizations build, govern, and scale AI solutions that deliver sustainable competitive advantage across industries such as BFSI, manufacturing, retail and CPG, automotive, healthcare, and life sciences. Founded in 2012, Altimetrik has more than 10,000 practitioners worldwide and serves over 200 active clients. Its work has driven more than 1,750 measurable outcomes and has been recognized by Constellation Research, Everest Group, and ISG. Applicants can learn more about Altimetrik’s services, culture, and innovation focus at altimetrik.com.
Role Description This is a full-time Senior AI Engineer role based in Pune City, with a hybrid work arrangement that allows a mix of onsite and work-from-home days. The Senior AI Engineer will design, develop, and deploy advanced AI models and solutions, collaborating with cross-functional product and engineering teams to integrate AI capabilities into production systems. Day-to-day responsibilities include building and optimizing machine learning pipelines, applying pattern recognition and neural network techniques, and working on NLP-driven features for enterprise applications. The role involves writing high-quality, scalable code, conducting experiments, evaluating model performance, and ensuring robust monitoring, governance, and compliance of AI systems. The Senior AI Engineer will also mentor team members, contribute to architecture decisions, and collaborate with platform partners and internal stakeholders to leverage Altimetrik’s AI ecosystem effectively.
Required Skills
Strong foundation in Computer Science, with expertise in algorithms, data structures, and software development practices.
Hands-on experience with pattern recognition techniques and machine learning workflows for real-world applications.
Deep understanding of neural networks, including modern architectures (e.g., transformers, CNNs, RNNs) and training/optimization methods.
Practical experience with Natural Language Processing (NLP), including model training, evaluation, and deployment for text-based solutions.
Proficiency in programming languages commonly used in AI (such as Python, Java, or Scala) and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Experience building production-grade AI services on cloud platforms (e.g., Google Cloud, AWS, or Azure) and working with data platforms (e.g., Snowflake, Databricks).
Ability to design scalable architectures, work with APIs and microservices, and apply MLOps practices for CI/CD, monitoring, and model lifecycle management.

Work arrangement
Hybrid