Machine Learning/Artificial Intelligence Engineer

Intelliswift$120K — $150K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years experience in Machine Learning, Deep Learning, and NLP
  • Proficiency in TensorFlow, PyTorch, and other relevant ML libraries
  • Strong background in statistical modeling and data analysis
  • Hands-on experience in building and deploying machine learning models
  • Proficient in Python, Spark, Hive, and SQL
  • Experience with data science tools like Jupyter and RStudio

Responsibilities

  • Provide technical leadership and guide project vision
  • Translate client requirements into technical architectures
  • Design and implement big data analytics solutions
  • Gather requirements and perform feature engineering
  • Evaluate and optimize machine learning algorithms
  • Develop data collectors for big data platforms
  • Conduct production support and automation of processes

Benefits

  • Opportunity to work in the innovative Bay Area tech ecosystem
  • Gain experience with cutting-edge machine learning technologies
  • Collaborate with a talented team of data scientists
  • Chance to lead high-impact projects in a dynamic environment
  • Support for personal and professional growth
Full Job Description
Additional Note: Successful candidate will need to relocate to the Bay Area prior to remote start.

Must Haves:
• Machine Learning, Deep Learning, NLP
• TensorFlow, Scipy, PyTorch, OpenCV, OCR
• Numpy, SKlearn, Pandas
• Python, Spark, Hive, SQL
• Productionize model.

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.
• Strong Background in Statistical modeling, NLP and Machine Learning.
• Expertise in various facets of Client and NLP, such as classification, feature engineering, information extraction, clustering, semi-supervised learning, topic modeling and ranking.
• Strong Hands-on Experience in building, deploying and productionizing Client models using software such as Spark MLLib, TensorFlow, PyTorch, Python Scikit-learn etc. is mandatory
• bility to evaluate and choose best suited Client 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 RStudio, Jupyter, Zeppelin, PyCharm etc.
• Design and implement an integrated Big Data platform and analytics solution
• Design and implement data collectors to collect and transport data to the Big Data Platform.
• Good to have but not mandatory 4+ years of hands-on Development, Deployment and production Support experience in Hadoop environment.
• 4-5 years of programming experience in Java, Scala, Python.
• Proficient in SQL and relational database design and methods for data retrieval.
• Good to have but not mandatory building data pipelines using Hadoop components Sqoop, Hive, Spark, Spark SQL, HBase.
• Good to have but not mandatory experience with developing Hive QL, UDF's for analyzing semi structured/structured datasets.
• Good to have but not mandatory experience ingesting and processing various file formats like Avro/Parquet/Sequence Files/Text Files etc.
• Hands-on experience working in Real-Time analytics like Spark/Kafka/Storm
• Must have working experience in the data warehousing and Business Intelligence systems.
• Expertise in Unix/Linux environment in writing scripts and schedule/execute jobs.
• Successful track record of building automation scripts/code using Java, Bash, Python etc. and experience in production support issue resolution process.

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