Machine Learning AI Engineer
Position: Machine Learning AI Engineer
Duration: 12+ Months
Location: Remote
Must Haves
- Strong project experience in Machine Learning, Big Data, NLP, Deep Learning, RDBMS is must.
- Strong project experience with Amazon Web Services and Cloudera Data Platform is must.
- 4-5 experience building data pipelines using Python, MLLib, PyTorch, TensorFlow, Numpy/Scipy/Pandas, Spark, Hive,
- 4-5 years of programming experience in AWS, Linux and Data Science notebooks is must.
- Strong experience with REST API development using Python frameworks (Django, Flask etc.).
- Micro Services/Web service development experience using Spring framework is highly desirable
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
Position: Machine Learning AI Engineer
Duration: 12+ Months
Location: Remote
Must Haves
- Strong project experience in Machine Learning, Big Data, NLP, Deep Learning, RDBMS is must.
- Strong project experience with Amazon Web Services and Cloudera Data Platform is must.
- 4-5 experience building data pipelines using Python, MLLib, PyTorch, TensorFlow, Numpy/Scipy/Pandas, Spark, Hive,
- 4-5 years of programming experience in AWS, Linux and Data Science notebooks is must.
- Strong experience with REST API development using Python frameworks (Django, Flask etc.).
- Micro Services/Web service development experience using Spring framework is highly desirable
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