Compensation Overview

Salary Range: 180000 to 210000 (Currency: USD) (Pay period: per-year-salary)

How will you contribute?

• Technical Leadership:
• 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
• Product mindset while being aware and addressing customer challenges and business needs

People Management

• 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
• Collaborate with peer engineering leaders influencing outcomes with-in and outside team
• 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.
• Influence, Establish and Sustain Best Practices.
• Actively participate in team agile ceremonies and provide valuable inputs.
• Other duties as assigned.

Technical Requirements

• Good experience and Proficiency with JVM language (Java/Kotlin) and experience in Python
• 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

What do we offer?

• Healthcare insurance
• We provide medical, dental, and vision insurance, and a flexible spending account that allows you to set aside pre-tax dollars to pay for eligible out-of-pocket expenses.
• Personal time off
• A healthy work-life balance is critical to your success at the office. Smarsh offers a “take-what-you-need” time off policy as well as flexible work arrangements
• 401K Match
• Smarsh provides a 4% 401K match for which employees are fully vested on day one.
• Sabbatical: The Smarsh sabbatical programme provides a time to recharge, study or simply do something you are passionate about away from the workplace. Employees are eligible after six years of service.
• Recognition: We’re big on kudos for a job well done. Our employee-recognition programme enables co-workers to nominate their peers who best embody our core values for recognition