AI/ML Engineer

Location: Gurugram, Haryana, India | Experience: Mid-Senior Level (5-6 years)

About the Company

Stigasoft is a global AI, Machine Learning, and Digital Engineering technology partner helping enterprises accelerate digital transformation. The company builds AI-powered solutions, intelligent platforms, modern applications, scalable enterprise software, and high-performance engineering solutions for customers across the globe. Its capabilities span Generative AI, Agentic AI, business intelligence, enterprise mobility, cloud and DevOps, product engineering, cybersecurity, and software testing. Stigasoft constantly anticipates changing client needs and develops services that create practical business value. The company aims to be recognized as a world-class software solutions provider delivering high-quality services at competitive prices. Its culture is grounded in innovation, creative solutions, client partnership, excellence, continuous growth, and integrity. Teams are encouraged to take ownership, build trust, collaborate across disciplines, support inclusivity and equal opportunity, and invest in continuous learning and professional growth. Engineers join an environment where technical thinking is connected to measurable customer outcomes and durable digital transformation.

About the Role

As an AI/ML Engineer at Stigasoft, you will own the design, development, and productionization of machine learning solutions that help enterprise clients make faster, smarter, and more scalable decisions. You will translate business problems into measurable modeling strategies, build reliable data and inference workflows, and partner with software and platform engineers to move solutions from experimentation into production. Your work will span modern AI use cases, including Generative AI and intelligent platforms, while maintaining strong standards for performance, security, testing, and maintainability. Success means models and AI capabilities that operate reliably in real environments, improve customer outcomes, and create reusable engineering assets across engagements. You will contribute to a culture of ownership, collaboration, continuous learning, and practical innovation.

Key Responsibilities

• Own the end-to-end delivery of machine learning solutions, from problem framing and data preparation through validation, deployment, monitoring, and measurable business impact for enterprise clients.
• Design and productionize Generative AI, Agentic AI, predictive modeling, or intelligent automation capabilities using reliable pipelines, evaluation methods, and controls that support consistent real-world performance.
• Partner with product, software, cloud, and client teams to convert business needs into scalable AI architectures, clear success metrics, and delivery plans aligned with customer outcomes.
• Build maintainable services and workflows for training, inference, experimentation, and monitoring, improving reliability, latency, reproducibility, and operational efficiency across machine learning deployments.
• Investigate model quality, data issues, and production incidents through structured analysis, then implement improvements that strengthen accuracy, resilience, security, and trust in delivered solutions.
• Contribute reusable frameworks, technical documentation, code reviews, and engineering standards that raise delivery quality and accelerate adoption of AI capabilities across teams and client programs.

Essential Skills & Technologies

• Strong experience with Python and practical machine learning development, including supervised and unsupervised learning, feature engineering, model evaluation, and translating business objectives into measurable technical outcomes.
• Hands-on expertise with deep learning or modern AI frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or equivalent tools used to build production-ready solutions.
• Experience developing Generative AI or Agentic AI applications using large language models, prompt and context strategies, retrieval-augmented generation, embeddings, vector databases, or evaluation workflows.
• Proficiency with data processing, SQL, APIs, and software engineering practices required to create reliable training, inference, integration, and automation pipelines for enterprise environments.
• Working knowledge of cloud platforms, containers, CI/CD, MLOps, model monitoring, and deployment patterns that improve scalability, observability, reproducibility, and operational control.
• Ability to assess model performance, data quality, security, privacy, and failure modes, applying disciplined experimentation and testing to improve reliability and stakeholder confidence.

Additional Plus

• Experience delivering AI or machine learning solutions for enterprise clients across domains such as business intelligence, mobility, cybersecurity, software testing, or digital engineering.
• Familiarity with distributed systems, cloud-native architecture, Kubernetes, feature stores, experiment tracking, or production observability practices that support scalable AI platforms.
• Contributions to reusable libraries, technical communities, research, patents, publications, or open-source projects demonstrating sustained curiosity and practical innovation.

What You'll Bring

• You bring 5–6 years of hands-on experience building and deploying machine learning or AI solutions, with the judgment to balance model quality, delivery constraints, maintainability, and customer value.
• You bring strong analytical thinking and structured problem-solving, turning ambiguous enterprise challenges into clear hypotheses, measurable experiments, robust solutions, and decisions that stakeholders can act on.
• You bring an ownership mindset, communicating clearly with technical and non-technical partners while taking responsibility for quality, reliability, documentation, and the business outcomes of your work.
• You bring curiosity and continuous-learning habits, staying current with evolving AI methods and applying new ideas selectively to create secure, scalable, and useful products or client solutions.

Why Join Us

At Stigasoft, you will work at the intersection of AI, Machine Learning, and Digital Engineering, helping enterprise customers turn complex transformation goals into practical technology outcomes. The role offers meaningful ownership across the full AI lifecycle, from shaping the problem and designing the solution to deploying, measuring, and improving capabilities in production. You will work on modern areas such as Generative AI, Agentic AI, intelligent platforms, scalable enterprise software, cloud and DevOps, cybersecurity, and software testing. This breadth creates opportunities to deepen technical expertise while seeing how engineering decisions affect customers and their operations. The company’s culture values innovation, creative solutions, client partnership, excellence, continuous growth, and integrity. It also emphasizes trust, collaboration, inclusivity, equal opportunity, continuous learning, and professional development. You will be part of a team where your ideas are valued, your ownership is visible, and your work contributes to reusable solutions and durable digital transformation. The role provides competitive compensation and a growth-oriented environment for engineers who want to build impactful AI systems.

What We Offer

• Work on challenging AI, Machine Learning, and Digital Engineering problems for enterprise customers, with opportunities to contribute across Generative AI, Agentic AI, cloud, platforms, and modern applications.
• Grow through continuous learning, professional development, cross-functional collaboration, and exposure to diverse technology programs where strong engineering decisions create visible customer value.
• Join an inclusive, integrity-led culture that supports ownership, trust, equal opportunity, creative problem-solving, and competitive compensation.