Data Scientist / ML Engineer

We are seeking a highly motivated Data Scientist/ML Engineer with 6-8 years of experience in designing, developing, deploying, and managing AI/ML solutions at scale. The ideal candidate should possess strong expertise in the complete machine learning lifecycle, from data preparation and model development to production deployment, monitoring, and optimization.
Responsibilities:
Develop and deploy machine learning, deep learning, time-series forecasting, and generative AI solutions for business-critical use cases.
Lead end-to-end AI model development, including data acquisition, feature engineering, model training, validation, deployment, and monitoring.
Build scalable ML pipelines and production-grade AI applications using MLOps best practices.
Collaborate with product managers, business teams, data engineers, and software developers to deliver impactful AI solutions.
Implement model governance, versioning, performance monitoring, and retraining frameworks.
Integrate AI models into enterprise applications through APIs and cloud-native architectures.
Drive continuous improvement in model accuracy, reliability, explainability, and operational performance.
Success Measures:
Successful deployment and adoption of AI solutions.
Improvement in operational KPIs, forecast accuracy, and process efficiency.
Reliability, scalability, and performance of production ML models.
Business impact and value realization from AI initiatives.
Requirements:
Ideal Candidate: A hands-on AI professional capable of independently building, deploying, and scaling machine learning solutions in industrial settings
Strong expertise in Python, SQL, machine learning, deep learning, time-series forecasting, NLP, LLMs, RAG, and computer vision.
Hands-on experience with Scikit-Learn, TensorFlow, PyTorch, Pandas, and NumPy.
Experience with MLOps tools such as MLflow, Azure ML, Model Garden, Vertex AI (Gemini Enterprise), SageMaker, Kubeflow, Docker, Kubernetes, and CI/CD pipelines.
Knowledge and experience of Azure/AWS/GCP cloud platforms.
Experience deploying and managing ML models in production environments at enterprise scale.
Bachelor's or master's degree in computer science, data science, statistics, mathematics, engineering, or a related field.
6-8 years of hands-on experience in AI/ML solution development and deployment.
Proven track record of delivering production-grade AI solutions that create measurable business value.
Key Competencies:
Strong problem-solving and analytical skills.
Ability to translate business challenges into AI solutions.
Excellent communication and stakeholder management skills.
Ownership mindset with focus on execution and outcomes.
Ability to work effectively in cross-functional Agile teams.

Experience
6-10 yrs