Machine Learning AI Engineer

Must Haves-

• Strong project experience in Big Data platform with Amazon Web Services and Cloudera Data Platform is must.

• Strong experience with REST API development using Python frameworks (Django, Flask etc.) is must.

• Micro Services/Web service development experience using Spring framework is must.

• 4-5 years of programming experience in AWS, Linux and Data Science notebooks is must.

• Good project experience in Machine Learning, Big Data, NLP, Deep Learning, RDBMS is must.

• 4-5 experience building data pipelines using Python, MLLib, PyTorch, TensorFlow, Numpy/Scipy/Pandas, Spark, Hive

TECHNICAL KNOWLEDGE AND SKILLS:

Consultant resources shall possess most of the following technical knowledge and experience:

• Provide technical leadership, develop vision, gather requirements and translate client user requirements into technical architecture.

• 4-5 years of Strong programming experience in Python, Java, Scala, SQL.

• Proficient in Machine Learning Algorithms: Supervised Learning (Regression, Classification, SVM, Decision Trees etc.), Unsupervised Learning (Clustering) and Reinforcement Learning

• Strong Hands-on Experience in building, deploying and productionizing ML models using MLLib, TensorFlow, PyTorch, Keras, Python Scikit-learn etc.

• Hands-on experience building data pipelines using Hadoop components Sqoop, Hive, Spark, Spark SQL, HBase.

• Data Processing and Analysis experience with Pandas, NumPy, Matplotlib/Seaborn etc. and using Big Data technologies (Hadoop/Spark)

• Must have Natural Language Processing (NLP) and Computer Vision experience.

• Ability to evaluate and choose best suited ML algorithms, perform feature engineering and optimize Machine Learning Models is mandatory

• Strong fundamentals in algorithms, data structures, statistics, predictive modeling, & distributed systems is must

• Strong Experience with Data Science Notebooks like Jupyter, Zeppelin, RStudio. PyCharm etc.

• Strong Mathematics and Statistics Background (Linear Algebra, Calculus, Probability and Statistics)

• 4+ years of hands-on Development, Deployment and production Support experience in Hadoop environment.

• Proficient in Big Data, SQL, relational database and NoSQL database for data retrieval and analysis.

• Must have experience with developing Hive QL, UDF s for analyzing semi structured/structured datasets.

• Expertise in Unix/Linux environment in writing scripts and schedule/execute jobs.

• Experience with AWS and other cloud platforms.

• Experience using Git and Eclipse.

• Experience in creating and managing RESTFul API s using Python and Java frameworks.

• Experience in Docker and Kubernetes containerization.

• Hands-on experience ingesting and processing various file formats like Avro/Parquet/Sequence Files/Text Files etc.

• Successful track record of building automation scripts/code using Java, Bash, Python etc. and experience in production support issue resolution process.

PREFERRED SKILLS:

Machine Learning,

Big Data, NLP, Deep Learning,

Python,

MLLib,

PyTorch,

TensorFlow,

Numpy/Scipy/Pandas, Spark,

Hive,

Data Science Notebooks,

SQL,

API,

Unix/Linux,

AWS