Role Overview
We are seeking a visionary and hands-on
Algorithm Manager to lead our data science and algorithm engineering team. In
this role, you will bridge the gap between complex mathematical research and
scalable product implementation. You will be responsible for defining the
technical roadmap, mentoring a team of high-performing engineers, and ensuring
our algorithms drive significant business impact.
Key Responsibilities
l Team Leadership: Lead, recruit, and mentor a team of algorithm
engineers and data scientists. Foster a culture of technical excellence and
continuous learning.
l Technical Strategy: Define the long-term vision for algorithm
development, including machine learning (ML), optimization, or signal
processing (depending on the specific domain).
l Project Management: Oversee the end-to-end lifecycle of algorithm
development—from research and prototyping to production deployment and
monitoring.
l Cross-functional Collaboration: Work closely with Product, Hardware,
and Software Engineering teams to integrate algorithms into user-facing
products.
l Innovation: Stay at the forefront of AI/ML research, identifying new
technologies and methodologies that can give the company a competitive edge.
l Code Quality & Standards: Establish best practices for code
reviews, testing, and documentation within the algorithm team.
Required Qualifications
l Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a
related quantitative field.
l Experience: 7+ years of experience in algorithm development or
machine learning.
l 3+ years of experience in a leadership or people management role.
l Technical Proficiency: Expertise in Python, C++, or Java
l Deep understanding of ML frameworks (e.g., PyTorch, TensorFlow,
Scikit-learn).
l Strong foundation in linear algebra, probability, and optimization
theory.
l System Design: Proven track record of deploying large-scale
algorithmic systems in a production environment.
Preferred Skills (The "Plus"
Factors)
l Experience with Big Data technologies (Spark, Flink) or Cloud
platforms (AWS, GCP, Azure).
l A strong publication record in top-tier conferences (ICML, NeurIPS,
CVPR, etc.).
l Excellent communication skills with the ability to explain complex
technical concepts to non-technical stakeholders.
