- Location
- Chennai, Tamil Nadu, India
- Job type
- Full-time
Required skills
- Python
- Airflow
- AWS
- Azure
- containerization
- data ingestion
- data science
- deep learning
- Docker
- forecasting
- fraud detection
- GCP
- GitHub
- Kubeflow
- Kubernetes
- machine learning
- microservices
- NLP
- NumPy
- Pandas
- Ray
- Spark
- SQL
- TensorFlow
- Pytorch
- Vertex
- REST APIs
About the role
Best Apps Business Solutions Pvt Ltd™
Website:
bestappsbs.com
Job details:
Job Description:
- Design, train, and deploy machine learning and deep learning models for forecasting, recommendations, personalization, pricing optimization, fraud detection, and demand planning.
- Develop LLM powered solutions (RAG pipelines, agents, copilots) using internal and external data sources.
- Apply NLP, time series analysis, and predictive modeling to large scale enterprise datasets.
- Platform & Engineering
- Build and maintain end to end ML pipelines (data ingestion, training inference monitoring).
- Implement MLOps practices including CI/CD, model versioning, drift detection, and performance monitoring.
- Deploy AI solutions using cloud native services (GCP (preferrerd), Azure or AWS) with containerization (Docker/Kubernetes).
- Data & Analytics
- Partner with data engineers to curate, clean, and transform structured and unstructured data at scale.
- Optimize feature engineering and model performance using distributed computing frameworks (Spark, Ray, etc.).
- Business & Stakeholder Collaboration
- Work closely with product managers, architects, and business leaders to translate business problems into AI solutions.
- Support AI enablement across vendor and reseller ecosystems through insights and automation embedded in Xvantage.
- Governance & Responsible AI
- Ensure models comply with security, privacy, and responsible AI standards.
- Improve model explainability, fairness, and auditability for enterprise and regulatory needs.
Required Qualifications
Technical Skills
- Strong proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow, scikit learn).
- Experience building and deploying production ML models.
- Hands on experience with cloud AI services (such as GCP Vertex AI).
- Knowledge of LLMs, embeddings, vector databases, Google ADK and prompt engineering.
- Experience with REST APIs, microservices, and event driven architectures.
Data & Engineering
- Solid understanding of SQL and data warehousing concepts.
- Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, GitHub Actions, etc.).
- Experience with distributed data processing.
Education & Experience
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
- 3 to 7 years of experience in AI/ML engineering or applied data science (level dependent).
Preferred Qualifications
- Experience in digital commerce, supply chain, pricing, or distribution domains.
- Exposure to agentic AI frameworks and autonomous workflows.
- Knowledge of enterprise scale data governance and security practices.
- Experience supporting AI products used by thousands of users globally
Click on Apply to know more.
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