Position: Technical Lead/Manager - ML team
Company: Sift
Experience required: 5y
English level: upper

We are looking for Technical Leader with strong Java and big data skills, who will build and then manage the team in Ukraine.

**About the team:**
Our ML teams are part of our core Data Science and Machine Learning group and consist of Online and Offline ML teams.

The Online ML team is responsible for building and operating low-latency and data-intensive systems such as a feature store, feature extraction, ML model serving, and versioning systems. 

The Offline ML team is responsible for ML model release process, ML pipelines, model training, and validation.

**What we’re looking for:**
As the Technical Lead, you will start with individual technical contributions and later will take an engineering manager role for the hiring team in Ukraine.

During onboarding, you will be working on features technical design, and implementation, and collaborating with engineering managers and engineers from US-based teams. After your onboarding, we are going to hire engineers in Ukraine for our ML teams and you will take the engineering manager role for this team.

You value collaboration, transparency, and a Get Stuff Done mindset. As a leader, you understand the importance of these aspects of engineering success and lead by example. We are firm believers in servant leadership. 

**Tech stack:**
- Java
- GCP
- VertexAI
- Flink
- Dataflow
- Dataproc
- Airflow

**Opportunities for you:**
- Professional growth: quarterly Growth Cycles instead of performance review;
- Experience: knowledge sharing through biweekly Tech Talks sessions; 
- You will learn how to build projects that handle petabytes of data and have small latency and high fault tolerance;
- Business trips and the annual Sift Summit, in 2022, Summit took place in California;
- Remote work approach: you can choose where you work better.

**What would make you a strong fit:**
- 2+ years of hands-on experience managing BigData/backend teams and 7+ years of professional software development experience;
- Experience building highly available low-latency systems using Java, Scala, or other object-oriented languages;
- Knowledge of GCP or AWS cloud stack for web services and big data processing;
- Basic knowledge of MLOps on model release/training/monitoring;
- Conceptual knowledge of ML techniques;
- Experience initiating cross-functional collaboration between multiple functions (technical and non-technical);
- Experience hiring, mentoring, and developing top engineering talent;
- B.S. in Computer Science (or related technical discipline), or related practical experience.

**Bonus points:**
- Experience working with large datasets and data processing technologies for both stream and batch processing, such as Apache Spark, Apache Beam, Flink, and MapReduce;
- Experience in management and project management skills for planning and executing complex projects;
- Experience solving problems with production systems, and building solutions and automation to prevent them from reoccurring;
- Familiarity with practical challenges in ML systems such as feature extraction and definition, data validation, training, monitoring, and management of features and models;
- Practical knowledge of how to build end-to-end ML workflows;
- Experience with building an ML feature store for batch and real-time aggregation/serving.

**What you’ll do:**
- Building and operating low-latency and data-intensive systems;
- Designing, implementing, and operating large-scale distributed systems;
- Execute and improve the ML model release process;
- Collaborate with US-based ML teams and work with them in close partnership on core components of Sift products;
- Lead, manage, and mentor a team of talented, broadly-capable engineers who own key areas of our fraud detection platform, as well as systems that deliver unique, strategic insights in a challenging domain;
- Collaborate with other engineering teams to ensure we are working effectively and focusing on the right priorities;
- Help identify key strategic areas for investment in both product and technical backlogs;
- Demonstrate and embody a strong, abiding commitment to the highest cultural standard, focusing on inclusivity, collaboration, and teamwork.

**Benefits and Perks:**
- A compensation package that consists of financial compensation, a biannual 5% bonus, and stock options;
- Medical, dental, and vision coverage; 
- 50$ for sports and wellness;
- Education reimbursement: books, education courses, conferences;
- Flexible time off: we follow an unlimited vacation approach;
- Tuned work schedule to Ukraine time zone despite US offices location: biweekly demo sessions are optional for our team and we watch them from recording;
- Mental Health Days: additional day-offs;
- English courses and social activities inside the company that allow improving your public speaking and language.

**Our interview:**
We follow the same process for all teams, technical interview consists of 2 parts:
- 45 min phone interview with the head of the Ukraine R&D team;
- Virtual on-site interview: 4 sessions, 45 mins each, that cover engineering management, people management, system design, experience, and soft skills.
During our sessions, you will have the opportunity to learn about company culture, meet engineering leads from our team, and discuss distributed systems and distributed teams' work problems. You will have time for all interesting questions and transparency regarding your future responsibilities and the project.

**Let’s Build It Together:**
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.

This document provides transparency around the way in which Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy