Position: MLOps Engineer
Overall, 4 to 5 years of work experience as a Machine Learning Engineer or related role.
1.5 to 2 years of experience working as MLOps Engineer.
Understanding of data structures, data modelling and software architecture.
Familiarity and proficiency with machine learning frameworks (like PyTorch, TensorFlow, Keras, MxNet) and libraries (like scikit-learn, pandas).
Knowledge of CUDA, OpenCL, OpenGL, and OpenCV.
Proficiency in Python coding, knowledge in other programming languages is an added advantage.
Understanding and scripting on SQL/ NoSQL databases (e.g., MySQL, MangoDB)
Familiarity with various operating systems (e.g., Windows, Linux, UNIX)
Knowledge on Big Data & tools like Spark based - distributed training and inferencing.
Experience with deploying popular - highly scalable, distributed ML models and open-source projects.
Must have worked on one of the MLOps Tools: MLFlow, Kubeflow, DVC etc.
Deploying code fand using:
• Cloud Platforms - Azure, AWS, GCP.
• Standalone Systems (Using Flask/ FastAPI/ Docker/ Kubernetes etc.)
• Handling Code with respect to various languages - PMML, Pickle, ONNX etc.
Deep Neural Networks, Computer Vision and Natural Language Processing knowledge and understanding of Architecture/ Packages like Yolo, Mask-RCNN, NLTK, Gensim, SpaCy, CoreNLP etc. is a bonus.
Knowledge of text detection & OCR, human / face detection, generative models, reinforcement learning, video analytics, model compression / optimization.
Knowledge of math, probability, statistics, and algorithms.
Outstanding analytical and problem-solving skills.
Good team player and excellent written and verbal technical communication skills.
Preferable to have FMCG/CPG domain knowledge.
BE / BCA / BSc in Computer Science; Master's degree in the same stream is a plus.
Build ML (Dev/Test/ UAT) Pipelines using DEVOPS tools for Continuous Training/ Integration and Deployment.
Operationalize and Maintain the MLOps setup.
Handle Deployment of ML Models using any of the methods like Canary, Shadow etc.
Working with cross functional individuals like Data Engineers, SW Engineers to integrate the code as per the Deployment strategy.
Perform Sanity/ Smoke and Other Tests as per the Requirements to ensure the code functionality is working as expected.
Analyse logs generated as part of the AI code and develop methods to capture, raise red flag and communicate back to the respective stake holders.
Position: MLOps Engineer Qualifications: ïƒ˜ Overall, 4 to 5 years of work experience as a Machine Learning Engineer or related role. ïƒ˜ 1.5 to 2 years of experience working as MLOps Engineer. ïƒ˜ Understanding of data structures, data modelling and soft
Experience: 3.00-5.00 Years
Education: Bachelor Of Computer Application (B.C.A)