Average salary: Rs140,000 /yearly
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- ...and implementation of Machine Learning enabled product platforms- Ensure efficient and scalable data pipelines and ML workflows with MLOps practices- Collaborate with data scientists and engineers to bridge the gap between data and software development- Write clean, well-documented...Suggested
- Your role and responsibilities Role Overview: Hiring an ML Engineer with experience in Cloudera ML to support end-to-end model development, deployment, and monitoring on the CDP platform. Key Responsibilities: Develop and deploy models using CML workspaces Build...Suggested
- ...communication and collaboration skills Bonus Points Experience with cloud platforms (e.g., AWS, GCP, Azure) Experience with MLOps tools and methodologies Open-source contributions If you get to join us, what you get in the process would be invaluable opportunities...Suggested
- ...Optimize delivery processes and implement tools (Jira, Tableau, Power BI) for efficiency. Stay updated on emerging trends (Generative AI, MLOps) and integrate best practices. Reporting ~ Track KPIs (timeliness, budget, quality) and prepare executive reports....SuggestedFull time
- ...text generation, summarization, translation, etc.- Develop and deploy cutting-edge generative AI & Agentic AI applications- Implement MLOps practices - model training, evaluation, deployment, monitoring, and maintenance.- Integrate machine learning capabilities into existing...Suggested
- ...PaaS services – Storage, DB & AI Services Expertise in API development using Flask, FAST API Experience deploying enterprise applications using Kubernetes or Docker, working with CI/CD pipelines & MLOps Good-to-Have ~ Experience with Relational and NoSQL data...Suggested
- ...implement LangGraph-based agent workflows prompt engineering strategies and model evaluation frameworks Familiarity with DevOps/MLOps practices for AI systems Knowledge about latest Industry trends and techniques in AI GenAI and Cloud technology areas Required...SuggestedFull time
- ...CI/CD pipelines, containerization (Docker, Kubernetes), and cloud infrastructure (AWS preferred).- Experience working with DevOps and MLOps workflows is a strong plus.- Proficiency in Agile methodologies, with hands-on use of Jira, Azure DevOps (ADO), or similar tools.- Strong...SuggestedFull timeFlexible hours
- ...and ML engineers to deliver high-quality, production-ready GenAI solutions. Establish coding best practices, CI/CD pipelines, and MLOps integration for model deployment and monitoring. Conduct code reviews, performance tuning, and prompt optimization. Partner with...SuggestedFull time
- ...experience in developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.) Experience in MLOps and ML model deployment pipelines. Proficiency in programming languages like Python, and ML frameworks like TensorFlow, PyTorch,...Suggested
- ...workflows. Understanding of model evaluation A/B testing and performance tuning. Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps tools (Docker MLflow Kubeflow CI/CD pipelines). Strong problem-solving abilities and ability to work independently on complex...SuggestedFull time
- ...translate LLM research into robust services—focusing on retrieval-augmented generation (RAG), vector search, prompt engineering, and MLOps best practices. Role & Responsibilities Design and implement end-to-end GenAI features: data ingestion → embedding generation →...Suggested
- ...Professional certifications such as PMP, PgMP, or PSM. In-depth knowledge of the AI/ML development lifecycle and familiarity with MLOps principles and associated technologies. Industry-specific experience in a sector undergoing significant AI-driven transformation, such...SuggestedFull timeHybrid work
- ...Hands-on experience developing and deploying generative AI applications (e.g. conversational AI image synthesis) - Experience with MLOps including model deployment pipelines monitoring and maintenance - Proficiency in Python and ML frameworks such as TensorFlow and PyTorch...SuggestedFull time
- ...Engineering experience, including SQL and ETL pipelines.- Hands-on experience with Cloud platforms AWS, GCP, or Azure.- Experience with MLOps practices including CI/CD, Docker, Kubernetes, MLflow.- Strong understanding of model evaluation techniques and Responsible AI...SuggestedImmediate start
- ...ready AI platform with modular architecture and reusable components. Design and oversee multi-model orchestration, including LLMOps, MLOps, vector databases, and RAG pipelines. Ensure scalability, reliability, observability, and cost efficiency across all AI services....Long term contractFull time
- ...communication and collaboration skills Bonus Points Experience with cloud platforms (e.g., AWS, GCP, Azure) Experience with MLOps tools and methodologies Open-source contributions If you get to join us, what you get in the process would be invaluable opportunities...
- ...period only ~ Must be able to clear strict background verification (BGV) Nice-to-Have Skill Set Python for data processing, MLOps, or AI integrations Experience with MLOps pipelines and ML lifecycle management Exposure to LLM integration or AI model deployment...Full timeHybrid workWork at officeImmediate startShift workAfternoon shift
- ...Data Vault, lakehouse). Hands-on Python, PySpark, SQL & distributed systems (Spark, Kafka). ML platform experience (SageMaker, MLOps, pipelines & deployment). Multi-cloud experience (AWS + Azure) with data migration & modernization. Certifications Required:...Hybrid work
- ...embeddings, hybrid search, and multimodal AI Collaborate with Data Engineering for strong ETL/ELT pipelines Deploy models using MLOps: Docker, CI/CD, MLflow, Kubeflow, Airflow Work on cloud ML platforms: AWS SageMaker, GCP Vertex AI, Azure AI Lead client discussions...Hybrid work
