Staff Machine Learning Engineer

2 weeks ago

Ahmedabad, Gujarat, India Infraveo Full time

This is a remote position.

We are seeking a Staff Machine Learning Engineer to join our team at Infraveo. The Staff Machine Learning Engineer will set the technical direction of their team to build and deploy machine learning solutions. They will work closely with Product and Engineering partners in the development of the solution.

Responsibilities:

  • Design and test machine learning models to create highly accurate systems used in operations.
  • Write production-quality code.
  • Take ownership of key components ensuring that they meet the needs of the business.
  • Collaborate with senior management, product management, and other engineers in the development of the product.
  • Mentor team members to build the company's overall expertise.

Requirements:

  • 7 years of industry experience in applied Machine Learning.
  • Masters Degree or PhD in CS/ ML or related field.
  • 5 years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale.
  • Deep understanding of ML best practices (A/B testing, training/serving pipelines, feature engineering etc), algorithms/techniques (gradient boosting, deep neural networks, optimization, regularization), and experiment design.
  • Experience in at least one of these domains: price estimation, personalization, recommender systems, computer vision, fraud detection and authentication, marketing.
  • Extensive experience in scientific libraries in Python (numpy, pandas) and Machine Learning tools and frameworks (Scikit-Learn, Tensorflow, Keras, PyTorch).
  • Strong data engineering skills and experience working with large scale datasets.
  • Experience with big data tools (Apache Beam, Apache Kafka, Spark).
  • Experience with cloud technologies AWS, GCP or Azure.
  • Fluency in Python, SQL.

Preferred Requirements:

  • PhD preferred (CS ML AI or related field).
  • Background in applying ML techniques to solve real-world business problems in the retail sector.
  • Familiarity with MLOps tools and pipelines.
  • Impact-focused and passionate about delivering high-quality models.
  • Demonstrated leadership experience with the ability to lead and inspire a team.

Benefits:

  • Work Location: Remote.
  • 5 days working.

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