AI/ML Senior Engineer

Job Summary
Adecco is partnering with one of the most well-established and respected financial institution with a strong track record of success. They have a culture of innovation and continuous improvement, constantly looking for ways to improve their services and offerings. Our client is looking for a AI/ML Senior Engineer to design, build and deploy end-to-end machine learning solutions. Candidates would have the hands-on opportunity to build models, build engineer scalable, production-grade ML systems.

Main Responsibilities

• Collaborate with business stakeholders to understand use cases and define AI solution; work on Proof of Concepts wherever needed
• Engineer and deploy ML models into production using MLOps best practices (model versioning, monitoring, CI/CD, etc.).
• Build & maintain data pipelines and model performance for scalability and maintainability.
• Ensure all models adhere to organizational AI policies, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and occasional model building where needed.
• Automate model retraining, testing, and monitoring to ensure performance over time.
• Document ML workflows, governance checkpoints, and risk assessments.
• Partner across multiple teams to integrate solutions into enterprise platforms.

Qualifications and Profile

Mandatory:

• Have degree or master’s degree in the field of AI / ML and data science with proven ability to design and develop models
• 8+ years of experience in software development, data science and ML, with at least 3+ years in AI engineering roles.
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong programming skills in Python with Solid knowledge of AI/ML, including LLMs and data science libraries like pandas, scikit-learn, TensorFlow/PyTorch, etc.
• Experience with LLM Orchestration frameworks like Langchain, LangGraph, vLLM, LMDeploy.
• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)
• Experience with MLOps tools: MLflow, Airflow, Kubeflow, or similar.
• Familiarity with either of cloud platforms (GCP, AWS) for AI Solutioning and ML deployment.
• Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.
• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.
• Ability to communicate technical concepts to non-technical stakeholders.

Preferred skills:

• Experience with Responsible AI frameworks and bias/fairness testing.
• Exposure to feature stores, model registries, and data versioning.
• Knowledge of data privacy, anonymization, and compliance in regulated industries.

Next Step

• If interested, you can click on “Apply here” or write an e-mail to [email protected] with your updated resume.
• NOTE: - Only shortlisted candidates will be contacted back.

Dimple Jain

EA LIcence No.91C2918

Personnel Registration No. R22107270