ML Engineering Manager

Machine Learning Engineering Manager This is an exciting opportunity to joina cutting-edge Digital Communications and Data Intelligence company.

This role will be part of the product development team, building analytic services using models built by data science teams.

With a focus on driving the development, deployment and support of advanced analytics, the MLE Managerwill be responsible for both people management as well astechnical leadership.

Working closely with cross-functional teams, it will be essentialto collaborate with data scientists, product managers and others tounderstand business objectivesanddeliver high quality, secure and resilient cloud-basedanalytic solutions. Responsibilities :

• Perform Both Technical Leadership as well as People Management
• Collaborate with data scientists, software engineers and other stakeholders
• Leveraging in-house and third-party models, design dynamically scalable and efficient analytic services
• Lead by example; actively contribute to design, development, and support of analytic services in production environments
• Provide technical guidance and mentorship to team members
• Foster a culture of learning and innovation
• Proactivelycommunicate updates and risksto key stakeholders and align with business objectives
• Manage a team of Machine Learning Engineers; performance management, hiring and mentoring
• Manage multiple geographically dispersed teams
• Establish transparent goals and expectations for the team, offering consistent feedback and assistance to aid members in meeting their targets
• Recognize avenues for professional advancement and personal growth among team members, actively fostering their career progression within the company
• Cultivate cross-team collaboration, facilitating the exchange of expertise in line with principles
• Work alongside fellow engineering leaders to shape outcomes both within and beyond the team's scope
• Assess the advantages and drawbacks of different solutions, recommending the most effective course of action
• Identify recurring issues and proactively implement measures to tackle their underlying causes
• Engage in both internal and external code reviews, offering feedback to foster ongoing enhancements
• Advocate for, establish, and uphold best practices within the team
• Take an active role in team agile ceremonies, contributing valuable insights and inputs

Requirements and Desired Experience :

• Experience with Java Virtual Machine (JVM) language, (i.e Kotlin, Scala) as well as Python development experience
• Experience in Natural Language Processing, Machine Learning Ops and data pipelines
• Experience with ML frameworks / libraries like PyTorch, scikit-learn, TensorFlow, etc.
• Strong understanding of ML Algorithms, data analysis methodologies and Statistical techniques
• Possess aproduct mindset while being aware of and addressing both customer challenges and business objectives
• Experience with Model Servers like TensorFlow Serving, TensorFlow Extended (TFX), NVIDIATriton Inference server
• Experience working in AI / ML based analytics products
• Experience with Data processing, feature engineering and model evaluation techniques.
• Experience with cloud platforms; Amazon Web Services and / or Google Cloud
• Proficient in containerized platforms likeAmazon ECS, Helm, Docker and Kubernetes
• Experience with Amazon Sagemaker and Jupyter Notebooks
• Experience with Continuous Integration / Continuous Deployment(CI / CD) tools
• Exposure to and experience building Machine Learning applications and services with cloud scalability
• Experience with RDBMS (i.e. MySQL & Postgres) as well Kafka
• Experience with microservices & event-driven architecture
• Experience with monitoring and visualization tools, specifically Prometheus & Grafana
• Proficient in API design and experienceworking working with distributed systems

Compensation : $175k - $215k annual salary