AI/ML Engineer

Location: Gurugram, Haryana, India | Experience: Mid Level (3-5 years)

About the Company

James Darwin is a BPM and BPO company focused on building its future through a clear, forward-looking vision. As the organization develops its next phase, technology and intelligent automation are important levers for improving how business processes are understood, delivered, and scaled. The company is creating an environment where practical innovation can connect data, operational workflows, and measurable business outcomes. This role contributes to that direction by applying artificial intelligence and machine learning to real business challenges. You will work with stakeholders across a process-led organization, translating operational needs into dependable technical solutions. The opportunity is suited to an engineer who values practical impact, disciplined execution, and solutions that can move beyond experimentation into production. At James Darwin, your work will support the company’s ambition to build its future by strengthening the intelligence, efficiency, and adaptability of its business operations.

About the Role

As an AI/ML Engineer, you will own the delivery of machine learning solutions from problem definition through deployment, monitoring, and improvement. You will partner with business and operations stakeholders to identify high-value use cases, prepare reliable data, select appropriate methods, and turn models into usable products. The role combines software engineering, analytics, experimentation, and production ownership. Success means building solutions that are accurate, maintainable, adopted by users, and connected to measurable improvements in process quality, speed, cost, or customer experience. You will help establish repeatable standards for model development and deployment while communicating trade-offs clearly to technical and non-technical audiences.

Key Responsibilities

• Own the end-to-end delivery of AI and machine learning solutions, from use-case framing and data preparation through deployment, monitoring, and iteration, ensuring measurable operational or customer impact.
• Build robust data and feature pipelines that convert process and business information into reliable model inputs, improving data quality, repeatability, and confidence in production decisions.
• Develop, evaluate, and optimize machine learning models using appropriate statistical and deep learning techniques, balancing accuracy, explainability, latency, maintainability, and business value.
• Productionize models through clean software engineering, APIs, testing, version control, and deployment practices, ensuring solutions remain dependable as data, volumes, and operating conditions change.
• Establish monitoring for model performance, data drift, service health, and business outcomes, using evidence to trigger retraining, remediation, or product improvements before value declines.
• Collaborate with operations, product, engineering, and leadership stakeholders to translate business problems into prioritized AI initiatives, communicating assumptions, risks, trade-offs, and results with clarity.
• Contribute to responsible AI practices covering data governance, privacy, security, bias assessment, documentation, and human oversight, protecting trust while enabling practical automation at scale.

Essential Skills & Technologies

• Strong Python and software engineering capability, with experience using machine learning libraries such as scikit-learn, TensorFlow, or PyTorch to develop testable, maintainable solutions.
• Practical expertise in supervised and unsupervised learning, model evaluation, feature engineering, experimentation, and statistical reasoning, with the judgment to select methods based on business constraints.
• Experience with SQL, data processing, APIs, Git, and production deployment, plus familiarity with cloud, containerization, CI/CD, or MLOps practices that support reliable model operations.
• Ability to work with large or messy datasets, diagnose data quality issues, and create reproducible pipelines that make model inputs traceable, consistent, and fit for operational use.
• Clear communication and stakeholder management skills, including the ability to explain technical findings, quantify model limitations, and align delivery choices with measurable business outcomes.

Additional Plus

• Exposure to natural language processing, generative AI, computer vision, forecasting, or intelligent document and workflow automation would help accelerate high-value use cases in a BPM and BPO environment.
• Experience with platforms such as AWS, Azure, or Google Cloud, and tools including Docker, Kubernetes, MLflow, Airflow, or managed model services would strengthen production delivery.
• Familiarity with contact-center, customer-experience, process-mining, or enterprise automation problems would help connect technical solutions to operational performance and adoption.

What You'll Bring

• A bachelor’s degree in Computer Science, Engineering, Data Science, or a related discipline, combined with three to five years of hands-on experience building and deploying machine learning solutions.
• An ownership mindset that takes responsibility for outcomes, not only model metrics, and follows problems through discovery, implementation, adoption, monitoring, and continuous improvement.
• Strong analytical judgment and curiosity, enabling you to investigate ambiguous operational problems, identify meaningful signals, test hypotheses, and make decisions using evidence.

Why Join Us

James Darwin is building its future as a BPM and BPO company, creating an opportunity to apply AI and machine learning where technology can improve real operating outcomes. Your work will connect engineering discipline with business-process transformation rather than remaining limited to isolated prototypes. You will have the scope to influence how use cases are selected, how models reach production, and how performance is measured after launch. The role offers meaningful ownership across the complete machine learning lifecycle, from framing the problem to proving business value. Working in a hybrid setup in Gurugram, you will collaborate with stakeholders who understand operational needs and help shape practical, scalable solutions. This is an opportunity to grow as an applied AI engineer while contributing directly to an organization with a stated ambition to build its future.

What We Offer

• A hybrid AI/ML engineering role in Gurugram with ownership across experimentation, production delivery, monitoring, and measurable business outcomes.
• The opportunity to work on practical AI applications within a BPM and BPO environment, connecting machine learning with process improvement, automation, and customer or operational value.