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Quickhyre AI
AI/ML:Engineers & Architect
Quickhyre AI
Chennai•On-site•3-5 Yrs•2 hours ago
Job description
AI/ML EngineerEnterprise AILife Sciences
Overview
Experienced AI/ML Engineer to design, develop, and deploy scalable machine learning and AI solutions across digital ecosystem. Collaborate with data scientists, engineers, and domain experts to transform large datasets into actionable insights and AI-driven applications.
Responsibilities
- Design, develop, train, and deploy machine learning (ML) and deep learning (DL) models for life sciences and manufacturing use cases
- Collaborate with cross-functional teams to identify opportunities for AI/ML-driven automation and optimization
- Implement end-to-end ML pipelines – from data ingestion and feature engineering to model training, validation, and deployment
- Work with big data platforms (Databricks, Snowflake, AWS Sagemaker, Azure ML, etc.) to manage and process large-scale datasets
- Develop NLP, computer vision, or predictive analytics models for applications in research, digital labs, and customer analytics
- Collaborate with software engineering teams to productionize and integrate AI models into enterprise applications
- Conduct performance tuning, model monitoring, and continuous retraining as needed
- Stay updated with emerging trends in AI/ML technologies and tools
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field
- Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, XGBoost, or LightGBM
- Strong understanding of data structures, algorithms, and statistics
- Experience with cloud-based ML platforms – AWS SageMaker, Azure ML, or GCP Vertex AI
- Hands-on experience in MLOps – model versioning, CI/CD, and monitoring using tools like MLflow, Kubeflow, or Airflow
- Exposure to NLP, computer vision, or time-series forecasting techniques
- Excellent problem-solving, communication, and collaboration skills
Nice to have
- Experience in Life Sciences / Healthcare / Pharma / Biotech domains
- Familiarity with data engineering tools like Databricks, Apache Spark, or Snowflake
- Knowledge of GenAI and LLM fine-tuning (e.g., OpenAI, Hugging Face, LangChain)
- Experience deploying models as REST APIs or microservices using Flask/FastAPI
- Understanding of data governance, model ethics, and regulatory compliance in AI applications
Education
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field
Benefits
- Work on impactful projects driving innovation in healthcare and life sciences
- Collaborate with global teams across R&D, engineering, and data science
- Access to cutting-edge AI/ML platforms and technology ecosystem
- Inclusive, diverse, and innovation-driven culture