ML Tech Lead

Industry: Healthcare Services
Remote
Company size: 10K+
Full-time/Part-time

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Job description

A U.S.-based company that is providing extensive healthcare services to help patients lead healthy and more fulfilled lives, is looking for a ML Tech Lead. The selected candidate will be taking charge of developing and implementing machine learning models and systems with a group of data scientists and engineers. With the company's top-notch psychiatric and chemical dependency treatments, patients can get superior treatment and care. This position requires 4-6+ hours of overlap with the CST time zone. 

 

Job Responsibilities:

  • Develop and deploy cutting-edge machine learning solutions with the help of a team of data scientists and machine learning engineers
  • Work with cross-functional teams, offer technical direction, and spearhead the development of machine learning systems
  • Incorporate ML solutions into operational systems while working with software engineering teams
  • Create and put into practice ML development best practices, coding standards, and quality control procedures
  • Thorough testing and monitoring should be done to make sure that ML systems are reliable, scalable, and performant
  • Technical and non-technical stakeholders should be presented with documentation of technological solutions, methodology, and findings
  • Keep up with market developments and make suggestions for new techniques and technologies
  • Make sure security measures are created and put into place, and that data management procedures are followed
  • Maintain an acute awareness of the most recent developments in the area while ensuring the quality and scalability of ML solutions
  • Work on developing the solutions within the Azure ML ecosystem
  • Work together to identify the objectives of the ML project and to understand business requirements with stakeholders, product managers, and domain experts
  • Team members can improve and develop professionally if you give them technical advice and coaching
  • Drive the development of scalable and effective machine learning systems, including their architecture and implementation
  • Initiate, oversee, and implement data pipeline design, architecture, and execution for effective data intake, preprocessing, and feature engineering
  • Educate yourself on the most recent ML frameworks, tools, and methodologies
  • Ensure that the evaluation and selection of suitable ML models and algorithms are based on the needs and restrictions of the project

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 8-10+ years of relevant experience as an ML Tech Lead, data scientist, or in a leadership position involving ML
  • Extensive knowledge of machine learning frameworks, algorithms, and methods
  • Proficient experience with programming languages, like Python, R, Java, or C++
  • In-depth knowledge of well-known machine learning frameworks like TensorFlow, PyTorch, or scikit-learn
  • Fundamental understanding of the Azure ML environment
  • Working knowledge of the Azure cloud environment (Azure, Databricks) and how to set up a Data lake in it
  • Solid understanding of the principles and guidelines for software engineering
  • Established leadership abilities with the ability to guide and motivate a team
  • Powerful analytical and problem-solving skills
  • Excellent teamwork abilities to work well with cross-functional teams
  • Nice to have some background in developing scalable and distributed machine-learning systems
  • Experience with DevOps methodologies, big data technologies, and cloud platforms is a plus.
  • Some contributions to the ML community through publications, patents, or other means is nice to have
  • Expertise in leading customer dialogues, requirements gathering/workshop sessions, and product demonstrations
  • Prior experience working in the healthcare sector is desirable
  • Prolific project management and leadership experience in remote work
  • Excellent spoken and written English communication skills

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