ML Engineer
ML Engineer
arrise solutions (india) pvt. ltd.- Posted 7 hours ago
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Job Description
About the Role
The ML Engineer works within a global team of Data Scientists, delivering machine learning methods into production in the most efficient way possible. This role designs, develops, and maintains ML pipelines, implements monitoring and alert systems, and optimizes trained AI models for latency, memory, and throughput. Based in Hyderabad, Noida, or remote, the ideal candidate has in-depth knowledge of model management, experiment tracking, and MLOps practices.
Key Responsibilities
• Design, develop, and maintain ML pipelines, ensuring high reliability and scalability.
• Implement scalable machine learning infrastructure to deploy algorithms based on image, text, audio, and tabular data.
• Optimize trained AI models for latency, memory, and throughput.
• Develop CI/CD pipelines and containerize production applications.
• Automate existing workflows within the Data Science team.
• Monitor and troubleshoot production ML systems using alert systems.
• Collaborate with cross-functional teams across data and engineering to solve complex problem statements.
• Lead research initiatives to explore new methodologies and contribute to best MLOps practices.
Key Skills
• 2-5 years of experience, with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Strong proficiency in Python, with extensive experience in PyTorch or TensorFlow.
• Extensive knowledge of key machine learning metrics and optimization techniques.
• Strong knowledge of version control systems (Git, data versioning).
• Experience with model management and experiment tracking frameworks (e.g., MLflow, DVC, LakeFS).
• Strong knowledge and practical understanding of MLOps techniques.
• Prior experience deploying and monitoring scalable ML models, CI/CD pipelines, and containerization.
• Excellent problem-solving, analytical, and communication skills.
Good to Have
• Extensive experience with the Azure ecosystem, particularly Azure Machine Learning.
• Experience developing computer vision, text, audio, or tabular data models.
• Strong proficiency in Gitlab CI, Jenkins, Grafana, and Docker.
• Excellent software engineering skills in API design and concurrency.
The ML Engineer works within a global team of Data Scientists, delivering machine learning methods into production in the most efficient way possible. This role designs, develops, and maintains ML pipelines, implements monitoring and alert systems, and optimizes trained AI models for latency, memory, and throughput. Based in Hyderabad, Noida, or remote, the ideal candidate has in-depth knowledge of model management, experiment tracking, and MLOps practices.
Key Responsibilities
• Design, develop, and maintain ML pipelines, ensuring high reliability and scalability.
• Implement scalable machine learning infrastructure to deploy algorithms based on image, text, audio, and tabular data.
• Optimize trained AI models for latency, memory, and throughput.
• Develop CI/CD pipelines and containerize production applications.
• Automate existing workflows within the Data Science team.
• Monitor and troubleshoot production ML systems using alert systems.
• Collaborate with cross-functional teams across data and engineering to solve complex problem statements.
• Lead research initiatives to explore new methodologies and contribute to best MLOps practices.
Key Skills
• 2-5 years of experience, with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Strong proficiency in Python, with extensive experience in PyTorch or TensorFlow.
• Extensive knowledge of key machine learning metrics and optimization techniques.
• Strong knowledge of version control systems (Git, data versioning).
• Experience with model management and experiment tracking frameworks (e.g., MLflow, DVC, LakeFS).
• Strong knowledge and practical understanding of MLOps techniques.
• Prior experience deploying and monitoring scalable ML models, CI/CD pipelines, and containerization.
• Excellent problem-solving, analytical, and communication skills.
Good to Have
• Extensive experience with the Azure ecosystem, particularly Azure Machine Learning.
• Experience developing computer vision, text, audio, or tabular data models.
• Strong proficiency in Gitlab CI, Jenkins, Grafana, and Docker.
• Excellent software engineering skills in API design and concurrency.
More Info
Key Skills
Monitoring and alert systems
data versioning)
Model management
MLOps techniques
CI/CD pipelines
Version control systems (Git
Gitlab CI
ML pipelines
About Company
Skills:
Natural Language Processing, Python Frameworks, Deep learning architectures, Neural network design
Skills:
Python, LangChain, Azure OpenAI APIs, Chroma, Vector databases, FAISS, Ai, OpenAI, Pinecone, LlamaIndex
Skills:
Machine Learning, Nlp, Typescript, Docker, Python, AWS, MLops, Gcp, FastAPI, Azure, Backend Engineering, Kubernetes, Argo Workflows, Go, Claude, ML pipelines, Observability and telemetry, Generative AI, Applied AI, Golden datasets, Transformer-based models, ML workflows, RAG, Real-time ML applications, OpenAI, Model evaluation
Skills:
Python Programming, metrics, evaluation datasets, fine-tuning, LLM and AI fundamentals, Analytical Skills, AI agent architecture, prompt optimization, production ML AI systems, structured testing, benchmarks, model and LLM evaluation, root-cause analysis, model improvement
Skills:
Machine Learning, Natural Language Processing, Deep Learning, Numpy, Pytorch, Pandas, Python, Hugging Face Transformers, TesserAct, Scikit-Learn, LayoutLM, PaddleOCR