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Urgent! Neev Systems - Machine Learning Engineer Job Opening In Hyderabad – Now Hiring Neev Systems Private Limited

Neev Systems Machine Learning Engineer



Job description

<p><p>ML Engineer.<br/><br/><b>Experience </b>: 5+ Years.<br/><b><br/>Location :</b> Hyderabad.<br/><br/><b>About The Role :</b><br/><br/>We are seeking a highly skilled and experienced Machine Learning Engineer to lead the design and implementation of cutting-edge ML solutions across our organization.<br/><br/>You will be responsible for prototyping and taking models all the way from proof-of-concept to production deployment.<br/><br/>This role requires a deep understanding of ML algorithms, data processing pipelines, model optimization, and production-grade engineering practices.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Build and validate ML prototypes to solve real business problems.<br/><br/>- Develop, test, and optimize ML models using structured and unstructured data.<br/><br/>- Design and implement scalable data pipelines and model serving infrastructure.<br/><br/>- Continuously monitor, improve, and re-train models in production.<br/><br/>- Ensure reproducibility, versioning, and documentation of models and experiments.<br/><br/>- Evaluate and select appropriate ML tools, frameworks, and technologies to meet business requirements.<br/><br/>- Oversee the full ML lifecycle including data preparation, model development, training, validation, deployment, and monitoring.<br/><br/>- Collaborate with stakeholders to translate business needs into ML solutions.<br/><br/><b>Required Skills & Qualifications :</b><br/><br/>- Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field.<br/><br/>- 5+ years of professional experience with at least 3 years in machine learning and data science.<br/><br/>- Take at least one ML solution from idea to full-scale production deployment.<br/><br/>- Strong programming skills in Python, with experience in ML libraries like TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.<br/><br/>- Deep understanding of ML architecture patterns, data pipelines, and distributed systems.<br/><br/>- Experience with any of cloud platforms like AWS, Azure, or GCP and cloud-native ML tools (SageMaker, Vertex AI, Azure ML).<br/><br/>- Proficiency in Docker, Kubernetes, and other containerization/orchestration tools.<br/><br/>- Strong grasp of MLOps, model monitoring, and continuous integration/deployment pipelines.<br/><br/>- Hands-on experience with big data technologies like Spark, Hadoop, Hive, or similar.<br/><br/><b>Preferred Qualifications :</b><br/><br/>- Contributions to open-source ML projects or research publications.<br/><br/>- Experience with deep learning, NLP, computer vision, or reinforcement learning.<br/><br/>- Familiarity with data privacy, AI ethics, and governance frameworks.<br/></p><br/></p> (ref:hirist.tech)


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