Manager, Machine Learning Engineering

Job title:

Manager, Machine Learning Engineering

Company

Smarsh

Job description

Who are we?Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.SummaryCognition Analytics team is a part of the Cognition Product development team, building Analytic services using the models built by Data Science & Research teams. As an MLE Manager, you will be responsible for both technical leadership and people management, with a focus on driving the development, deployment and support of advanced analytics that deliver communications intelligence driving actionable insights as part of our FinTech and RegTech Product portfolio. You will work closely with cross-functional teams to understand business objectives collaborating with product managers, data scientists and other stakeholders to innovate and deliver high quality, secure and resilient cloud based SaaS Analytic solutions.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?

• 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

Smarsh is an equal opportunity and affirmative action employer. Qualified applicants will receive consideration without regard to their race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Smarsh invites all qualified and interested applicants to apply for career opportunities. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions. including the frequency of functions.About our cultureSmarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.

Expected salary

Location

London

Job date

Thu, 24 Oct 2024 22:43:38 GMT

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