Machine Learning Product Engineer

Key Skills

Apache Cassandra, Apache Hadoop, AWS, Azure, Big Data Technology, C++, Deep Learning, Effective communication skills, Infrastructure as code, Leadership Skill, Machine learning techniques, Python Programming, SPARK Programming

Job Description

• Develops and maintains technical solutions that adhere to engineering and architectural design principles while meeting business requirements. Provides technical expertise with a focus on efficiency, reliability, scalability, and security; includes planning, evaluating, recommending, designing, operationalizing, and supporting solutions in compliance with enterprise and industry standards.

  Customer Accountabilities:

  • Leverage deep technology expertise for own area of specialization to deliver and ensure that all areas across the organization that provision, manage and support various technologies have the necessary tools, processes and documentation required to effectively execute on their respective mandates 
  • Execute on Engineering strategy as it relates to the introduction of tools and the automation of build, test, release and configure activities across Application, Platform and Infrastructure
  • Partner with the Operations team to automatically integrate with appropriate tools and processes as part of automated/self-serve Application, Platform or Infrastructure releases
  • Work with partners across Technology and apply in-depth understanding of relevant business needs to identify and leverage synergies across the various areas
  • Act as the expert or lead innovator and agent of change for the programs and services under management
  • Work with other teams to implement best practices for engineering and management
  • Work with vendor platform providers and engineering peers to keep abreast of trends, products, frameworks, and applications
  • Identify and effectively manage stakeholder engagement and impacts across the enterprise
  • Interpret client needs, assess engineering related requirements and identify solutions to non-standard requests

  Shareholder Accountabilities:

  • Apply best practices and knowledge of internal / external business issues to improve products or services in own discipline
  • Monitor and control costs within own work
  • May interact with governance and control groups, (e.g. regulatory / operational risk, compliance and audit) to provide subject matter expertise and consult on risk issues / items related to Engineering technology and tools
  • May develop and/or contribute to negotiations of third party contracts/agreements
  • Maintain knowledge and understanding of external development, engineering and emerging solutions, market conditions and their impact
  • Proactively identify emerging technologies and innovative solutions for building more robust platform domains
  • The Machine Learning Product Engineer team at Layer 6 focuses on building industry-leading data-centric systems and model delivery systems. Our solutions include data pipelines, feature data lake, systemic data validation and automation of key activities in model delivery including model validation, shakedown, inference, and maintenance.
  • We are looking for experienced Machine Learning Product Engineers (MLPE) who have worked under tight deadlines and on challenging tasks. The ideal candidate is a strong coder with solid data engineering experience. They should also have expertise in machine learning, system design and devops.
  • The candidate will design and implement components of data and model delivery system and lead by example. The candidate will interact with machine learning scientists, the infrastructure team and data sources team to develop systems that will satisfy the needs of machine learning projects.
  • Implement complex data-centric solutions, including extremely complex and large data set verification, transformation and feature generation, to ensure continuous high-quality input for the model development
  • Build model delivery systems, including inference pipeline, automatic model validation reports generation, automatic model performance monitoring and model retraining, to ensure fast model productionization and reliable production system
  • Maintain the model in production and ensure the data/model related knowledge continuation within L6

  Job Requirements:

  Employee/Team Accountabilities:

  • Continuously enhance knowledge/expertise in own area and keep current with emerging industry trends, new technologies and best practices in the external market that can contribute to delivering effective client solutions
  • Prioritize and manage own workload in order to deliver quality results and meet timelines
  • Support a positive work environment that promotes service to the business, quality, innovation and teamwork and ensure timely communication of issues/ points of interest
  • Participate in knowledge transfer with senior management, the team, other technical areas and business units
  • Work effectively as a team, supporting other members of the team in achieving business objectives and providing client services
  • Identify and recommend opportunities to enhance productivity, effectiveness and operational efficiency of the business unit and/or team

  Breadth and Depth:

  • Expert knowledge of specific domain or range of engineering frameworks, technology, tools, processes and procedures, as well as organization issues
  • Expert knowledge of TD applications, systems, networks, innovation, design activities, best practices, business / organization, Bank standards, and may fulfill a governance role
  • Expert knowledge and experience in own discipline; integrates knowledge of business and functional priorities
  • Acts as a key contributor in a complex and critical environment
  • May provide leadership to teams or projects; shares expertise
  • Applies in-depth skills and broad knowledge of the business to address complex problems and non-standard situations
  • Generally reports to a Senior Manager or above

  Experience and/or Education:

  • University or post-graduate degree
  • Strong academic background (e.g., computer science, engineering)
  • 7 + years relevant experience

  Additional Information:

  Required Technical Skills

  • BSc+ in Computer Science, Math, Physics, or similar
  • 2+ years of extensive programming experience, at least 1 year in building production data systems
  • 1+ year experience of building machine learning production system
  • Strong experience with major Big Data technologies and frameworks including but not limited to Hadoop, MapReduce, Spark, Cassandra, Kafka, Elasticsearch
  • Good knowledge of Machine Learning and Deep Learning
  • Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting
  • Strong experience with Scala and Java 8

  Nice to have Skills

  • C++, Python experience
  • Experience in systems/infrastructure projects on AWS and Azure

  Benefits

  • Entrepreneurial and inclusive culture
  • Excellent health coverage and pension plan
  • Four weeks paid vacation
  • Catered lunches twice a week over machine learning talks