Remote Manager, Machine Learning Engineering

Summary

Join the Cognition Analytics team as an MLE Manager, leading technical leadership and people management, driving advanced analytics development, deployment, and support for FinTech and RegTech Product portfolio.

Requirements

• Good experience and Proficiency with JVM language (Java/Kotlin)
• Experience in NLP, ML-Ops and data pipelines
• Experience with ML frameworks/libraries such as TensorFlow, PyTorch, scikit-learn
• Strong understanding of ML Algorithms, Statistical techniques, and data analysis methodologies
• Experience with Data processing, feature engineering and model evaluation techniques
• Experience in cloud platforms like Amazon Web Services & Google Cloud
• Experience with Amazon Sagemaker and Jupyter Notebooks
• Experience with Model Servers such as Triton Inference server
• Experience working in AI/ML based Analytics products
• Experience in microservices & event-driven architecture
• Exposure and experience in building ML applications/services with cloud scalability
• Experience in Kafka and RDBMS such as MySQL & Postgres
• Proficient in containerized platforms like Docker, Helm & Kubernetes
• Experience in CI/CD tools like Bamboo, ArgoCD
• Experience in Prometheus & Grafana
• Proficient in API design
• Proficient in working with distributed systems

Responsibilities

• Collaborate with data scientists, software engineers and other stakeholders to design dynamically scalable and efficient Analytic services leveraging in-house and third-party models
• Lead by example by actively contributing to design, development, and support of Analytic services in production environments following Smarsh standard Engineering methodology and processes
• Provide Technical guidance and mentorship to team members fostering culture of learning and innovation
• Communicate updates and risks proactively on the progress of team’s commitments to key stakeholders and aligning with overall business objectives
• Championing Quality of Product and Service adopting standards, methods, metrics, and processes ensuring continuous assessment, learning and improvement
• Manage a team of ML engineers including hiring, mentoring and performance management
• Manage multiple teams across geographic regions
• Set clear goals and expectations for the team and provide regular feedback and support to help team members achieve objectives
• Identify opportunities for professional development and growth for team members and support their career advancement within the organization
• Foster cross collaboration, promoting knowledge sharing aligning to OneSmarsh
• Can weigh the pros and cons of various solutions and propose the best path
• Recognize issue patterns and implement proactive measures to address the root causes
• Manage task lifecycle using tools like JIRA
• Participate in internal & external code reviews, provide feedback for continuous improvement

Benefits

• We value our people and offer a competitive salary along with company bonus
• Strong maternity and paternity scheme
• A workplace pension scheme
• Take what you need holiday package
• Private medical insurance
• Dental plan
• Group life assurance
• Group income protection
• Employee assistance programme
• A monthly wellness allowance
• Adoption assistance
• Stock options