ML Architect

Industry: Entertainment
Company size: 1-10

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Job description

A rapidly-growing company that is determined to transform the media and production industry with their cutting-edge technology and solutions, is looking for an experienced ML Architect. The selected candidate will be in charge of initiating, overseeing, and implementing data pipeline design, architecture, and execution for effective data intake, preprocessing, and feature engineering. The company is developing an AI system that will help studios in transforming the pre-production processes currently used for movies and TV shows. This will be a long-term position and requires a significant overlap with the CST time zone. 


Job Responsibilities:

  • Lead the design and implementation of data-driven machine learning solutions, provide strategic technical leadership
  • To match technological initiatives with overarching business goals, work collaboratively with cross-functional teams
  • Utilize your practical data science and text processing knowledge, paying special attention to NLP, LLMs, and pertinent models
  • Make wise choices on feature engineering, model selection, and optimization.
  • Showcase an in-depth knowledge of the cloud environment's Datalake setup process
  • Ensure that security measures are created and put into place and that data management and data governance best practices are followed
  • Establish reliable MLOps pipelines for effective model deployment, management, and monitoring
  • To smoothly integrate machine learning models into production environments, work with DevOps teams
  • Engage in hands-on machine learning model and proof-of-concept implementation
  • Mentor the team, helping them overcome difficult technical obstacles and promoting learning
  • Control the whole machine learning project lifecycle, from conception to deployment and ongoing upkeep
  • To guarantee successful project execution, work together with the business to define project milestones, timeframes, and deliverables
  • Showcase a deep knowledge of technical project management for ML projects
  • Ensure that technical and non-technical stakeholders are presented with documentation of technological solutions, methodology, and findings
  • 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
  • Work together to identify the objectives of the ML project and to understand business requirements with stakeholders, product managers, and domain experts
  • Create, guide, and manage a brilliant group of engineers, data scientists, and other technical experts
  • Establish a collaborative atmosphere, promote creativity, and foster team success
  • Align technical approaches with organizational goals, leveraging your business savvy to have the greatest impact
  • Work together with stakeholders to determine high-impact initiatives and establish a strategic order for them
  • Utilize your startup experience to succeed in a dynamic, fast-paced atmosphere
  • Show flexibility, initiative, and resiliency in achieving achievements in the face of uncertainty
  • Analyze and choose the best technology stacks, frameworks, and tools for your project
  • To inform your technology choices, keep up with market trends and new technological developments
  • By showcasing strategic thought, leadership, and technical foresight, show that you have the potential to advance into the position of CTO

Job Requirements:

  • Ph.D./Master’s degree in Engineering, Data Science, Computer Science (or equivalent experience)
  • At least 5+ years of relevant experience as an ML Architect
  • Prolific experience and knowledge of Machine Learning technologies and Python programming
  • Strong foundation in technical leadership, text processing, MLOps, and data science
  • Prior experience facilitating customer dialogues, requirements-gathering workshops, and product demonstrations
  • Solid knowledge of the principles and guidelines for software engineering
  • Demonstrable experience successfully managing machine learning projects from beginning to end, including data science, project management, and practical implementation
  • Strong knowledge of machine learning frameworks and libraries (such as PyTorch and TensorFlow)
  • In-depth knowledge of one or more container technologies like Docker or Kubernetes as well as cloud platforms like AWS, Azure, or GCP
  • Successful track record in startup contexts that shows flexibility, creativity, and a results-oriented mindset
  • Excellent business sense, the capacity to work well with stakeholders, and excellent communication abilities
  • Strong strategic thinking with the capacity to lead business teams, inspire innovation, and promote growth
  • Prior practical experience with text processing utilizing NLP, LLMs, and other relevant models is nice to have
  • Ability to foster domain-specific creativity with the help of prior media industry experience is desirable
  • Fluent in spoken and written English communication

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