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
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