Sr. Machine Learning Engineer

Company Overview:Kavtech Solutions (Pvt) Limited is a leading Data & AI company, recognized for its expertise in Data Visualization, Data Warehousing, Data Integration, Business Intelligence, and Machine Learning/Artificial Intelligence. With a strong portfolio of partnerships and development contracts with global clients, Kavtech Solutions is at the forefront of delivering innovative and data-driven solutions across various industries.About the RoleWe are seeking an experienced AI/ML Architect to design and lead enterprise-scale AI and ML solutions on AWS. The ideal candidate will have strong expertise in Amazon SageMaker for traditional ML pipelines and Amazon Bedrock for Generative AI use cases. This role requires technical leadership, solution architecture, and the ability to collaborate with business stakeholders, data engineers, and ML teams to deliver scalable, secure, and cost-efficient AI/ML systems.Key ResponsibilitiesArchitect and design end-to-end ML and GenAI solutions using AWS services (SageMaker, Bedrock, Lambda, Step Functions, Glue, Redshift, S3).Define and implement ML pipelines covering data ingestion, preprocessing, training, hyperparameter tuning, deployment, and monitoring.Leverage Amazon Bedrock to design and deploy Generative AI solutions such as chatbots, copilots, RAG (retrieval-augmented generation) systems, and content generation tools.Select appropriate foundation models (Claude, Llama, Titan, etc.) and fine-tune/integrate them with enterprise data.Ensure solutions are secure, scalable, and cost-optimized, following AWS Well-Architected Framework.Collaborate with stakeholders to gather requirements and translate them into architectural blueprints and technical roadmaps.Provide technical leadership and mentorship to ML engineers, data scientists, and developers.Establish best practices for model governance, monitoring, versioning, and CI/CD of ML workloads.Stay updated with emerging AI/ML technologies, AWS services, and industry trends to drive innovation.Required Skills & QualificationsBachelor’s or Master’s degree in Computer Science, AI/ML, Data Engineering, or related field.8+ years of professional experience in data engineering, ML engineering, or AI solution architecture.Proven expertise in AWS SageMaker (training, deployment, pipelines, feature store, monitoring).Strong experience with Amazon Bedrock and building GenAI applications.Hands-on skills in Python, PyTorch/TensorFlow, and SQL.Solid understanding of LLMs, prompt engineering, RAG, and fine-tuning techniques.Experience with data pipelines and integration (Glue, Redshift, Athena, EMR).Familiarity with DevOps/MLOps practices (CI/CD, IaC with Terraform/CloudFormation, model registry, monitoring).Strong knowledge of security, IAM, encryption, and compliance in cloud environments.Excellent leadership, communication, and stakeholder management skills.Preferred Skills (Nice-to-Have)AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect – Professional.Experience with LangChain, Vector Databases (Pinecone, Weaviate, FAISS), or Knowledge Graphs.Exposure to streaming platforms (Kafka, Kinesis) and real-time ML systems.Knowledge of MLOps platforms (MLflow, Kubeflow, etc.).Perks and Benefits:Competitive salary accompanied by an attractive benefits package.Paid annual leaves to promote work-life balance.Health insurance (OPD & IPD)Free lunch and gym allowance to support a healthy lifestyle.Yearly performance-based increments to recognize your hard work.Learning allowance to facilitate your professional growth.Participation in company-sponsored events to foster a vibrant work culture.