Job
Description
As a ML/Dev Ops Engineer at DHI Consultancy, you will be responsible for the following: - Experience: You should have 5 to 10 years of experience in ML Engineering, MLOps, or DevOps roles with a focus on machine learning systems. - Immediate Joiner: You must be able to start immediately or within a very short notice period. - MLOps Tools: Expert-level proficiency with mlFlow, Seldon, and Kubeflow is required. - Data & Feature Engineering: Strong practical experience with Databricks and Tecton (or similar feature stores) is essential. - Cloud & Infrastructure: Deep knowledge of AWS services for computing, storage, networking, and security is necessary. - CI/CD & Automation: Proven ability to build and manage automated pipelines using Jenkins. - Programming: Excellent coding skills in Python are expected. - Monitoring: Experience implementing monitoring solutions with Grafana (or similar tools like Prometheus) is a plus. --- In your role as a ML Senior Engineer at DHI Consultancy, your responsibilities will include: - Lead end-to-end design, training, and deployment of ML and DL models. - Work on NLP, classification, clustering, forecasting, recommender systems, and safety models. - Handle model evaluation through A/B testing, offline/online metrics. - Collaborate with engineering and product teams for integration. - Mentor junior engineers and conduct knowledge-sharing sessions. - Ensure scalability, cost-effectiveness, and performance optimization. Your required skills for this position are: - Strong background in Data Science, ML, AI, Statistics, Deep Learning, MLOps. - Hands-on experience with TensorFlow, PyTorch, MLlib, Databricks. - Expertise in Python, SQL, Spark, Kubernetes, Jenkins, Prometheus. - Proven experience in deploying large-scale ML systems. - Strong communication and leadership skills. Qualifications include: - Masters degree in Computer Science, Data Science, Statistics, or equivalent. - 5+ years of hands-on experience in production-level ML solutions. --- As a PX-Gen AI Engineer-1 (Hybrid) at DHI Consultancy, your key responsibilities will involve: - Fine-tune and optimize Large Language Models (LLMs) for specific use cases. - Deploy Gen AI models in production using AWS/Azure and Docker. - Build and maintain RESTful APIs with Flask/FastAPI for AI services. - Implement NLP-driven solutions with search and indexing capabilities. - Evaluate model performance, run experiments, and apply Agentic AI frameworks. - Collaborate across teams for integration and scalability of AI systems. - Research and integrate latest advancements in Gen AI and NLP. Your required skills for this position are: - Strong programming in Python. - Hands-on with LangChain, LangGraph, PyTorch, SpaCy, DSPy. - Cloud integration experience with AWS/Azure. - API development using Flask, FastAPI. - Knowledge of Agentic AI, LLM evaluation, Docker, MCP. Qualifications include: - B.Tech/M.Tech/Masters in Computer Science or AI-related field. - 5-7 years of experience in ML/AI with a strong focus on Gen AI. As a ML/Dev Ops Engineer at DHI Consultancy, you will be responsible for the following: - Experience: You should have 5 to 10 years of experience in ML Engineering, MLOps, or DevOps roles with a focus on machine learning systems. - Immediate Joiner: You must be able to start immediately or within a very short notice period. - MLOps Tools: Expert-level proficiency with mlFlow, Seldon, and Kubeflow is required. - Data & Feature Engineering: Strong practical experience with Databricks and Tecton (or similar feature stores) is essential. - Cloud & Infrastructure: Deep knowledge of AWS services for computing, storage, networking, and security is necessary. - CI/CD & Automation: Proven ability to build and manage automated pipelines using Jenkins. - Programming: Excellent coding skills in Python are expected. - Monitoring: Experience implementing monitoring solutions with Grafana (or similar tools like Prometheus) is a plus. --- In your role as a ML Senior Engineer at DHI Consultancy, your responsibilities will include: - Lead end-to-end design, training, and deployment of ML and DL models. - Work on NLP, classification, clustering, forecasting, recommender systems, and safety models. - Handle model evaluation through A/B testing, offline/online metrics. - Collaborate with engineering and product teams for integration. - Mentor junior engineers and conduct knowledge-sharing sessions. - Ensure scalability, cost-effectiveness, and performance optimization. Your required skills for this position are: - Strong background in Data Science, ML, AI, Statistics, Deep Learning, MLOps. - Hands-on experience with TensorFlow, PyTorch, MLlib, Databricks. - Expertise in Python, SQL, Spark, Kubernetes, Jenkins, Prometheus. - Proven experience in deploying large-scale ML systems. - Strong communication and leadership skills. Qualifications include: - Masters degree in Computer Science, Data Science, Statistics, or equivalent.
