Lead Machine Learning Engineer
UK - London
Applications have closed
Smarsh
Helping companies manage the risk in their electronic communications. Cloud-based capture, archiving and supervision solutions across more than 80 channels.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.
Summary
As a Lead Machine Learning Engineer, you will play a pivotal role in leading and driving the implementation of advanced analytics that delivers communications intelligence. This will drive actionable insights and solutions as part of our FinTech and RegTech Product portfolio. You will be part of a cross-functional agile team of talented ML engineers collaborating closely with product managers, data scientists and other stakeholders to deliver high quality, secure and resilient SaaS products.
The Machine Learning Engineering function is responsible for ensuring Smarsh can run state-of-the-art enterprise-grade machine learning at scale in a cost-effective manner. The Machine Learning Engineering Group develops and maintains the ML infrastructure, tooling, and analytic services to power intelligent applications.
How will you contribute?
- 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 for Fintech/Regtech domain
- 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, Argo CD
- Experience in Prometheus & Grafana
- Proficient in API design
- Proficient in working with distributed systems
What will you bring?
- Collaborate with cross-functional teams to design complex solutions and integrate multiple software products to solve high-level challenges.
- Act as a subject-matter expert in machine learning, fintech, and Regtech domains, providing technical leadership, insights, and guidance to internal teams and external stakeholders.
- Can weigh the pros and cons of various solutions and propose the best path.
- Work closely with Product Management and engineering teams to define and implement features in a fast-paced environment with careful attention to quality, scalability, and maintainability.
- Can break down complex technical solutions into simple abstractions.
- Influence Principal Engineers/Product Managers on product designs.
- Can investigate and solve complex bugs, performance, security, and scalability issues.
- Actively participate in troubleshooting and fixing Production Issues following the incident management process.
- 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 and receive feedback for continuous improvement.
- Influence, Establish and Sustain Best Practices.
- Mentor and coach team members.
- Actively participate in team agile ceremonies and provide valuable inputs.
- Other duties as assigned.
Additional Eligibility Qualifications
- Strong understanding and experience in continuous software delivery.
- Strong understanding of ML business and technology domain.
- Expert programming skills in relevant languages.
- Deep understanding and experience in software architecture/software engineering.
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 program provides a time to recharge, to study or simply a time to 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 program enables co-workers to nominate their peers who best embody our core values for recognition
About our culture
Smarsh 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs Architecture AWS CI/CD Data analysis Data pipelines Distributed Systems Docker Engineering Feature engineering FinTech GCP Google Cloud Grafana Helm Java Jira Jupyter Kafka Kubernetes Machine Learning Microservices ML infrastructure MLOps MySQL NLP Pipelines PostgreSQL Python PyTorch RDBMS SageMaker Scikit-learn Security Statistics TensorFlow
Perks/benefits: 401(k) matching Career development Flex hours Flexible spending account Flex vacation Health care Insurance
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