Machine Learning engineer
Roles and responsibilities
Code, train, evaluate and deploy machine learning models that integrate with the complete software solution.
Computer Science / Information echnology is required
M tech / Ph specialization in artificial intelligence / machine learning is preferable Pre-requisites mentioned below
Work-experience is preferable, but we are looking for expertise rather experience in number of years
Candidate must be good at programming and be able to adapt to any of the basic programming languages like C, C++, Python, Matlab, R, Julia, Java, Go, Rust etc.
Candidate must have mastery of basic computer science concepts like data structures, algorithms, databases, relational algebra (SQL), operating systems, computer architecture, computer networks.
Candidate must be comfortable in programming on GNU/Linux in a high performance computing (HPC) setups like multicores, clusters, GPUs, etc.
Candidate must be able to grasp concepts from latest research papers and implement them in a short time
Candidate must have a specialization in AI / ML and should have mastery over the topics in the prerequisites section
Candidate must be familiar with ML programming frameworks and libraries and should be able to quickly learn and adapt to the newly emerging ones
Some of the tools to be familiar with include
Python, Julia, R, jupyter, Pandas, PySpark, numpy, matplotlib, seaborn, streamlit, afka
Core Computer Science
C, C++, Python,Java, Scala, Network, igraph, MySQL, PostgreSQL, Linux, Mac, indows
Pyorch, ensorflow, scikit-learn, Goost, LightGM
Artificial Intelligence OpenC, dlib. scikit-image, nltk, SpaCy, faiss, flann, kaldi, sphinx, librosa
Systems / Computing OpenMP, MPI, Spark, CUA, AS, GCloud, Azure, Mosquitto, Paho, Jetson Nano Software engineering
Docker, Git, JIRA, MLOps toolkits
Machine Learning Engineers