Sr ML Engineering Manager, Search - Services Special Projects

Socket.dev

Sunnyvale (CA)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

Socket.dev is seeking a Search Engineering Manager & Lead to own the architecture for large-scale, low-latency search infrastructure. You will guide query understanding, hybrid retrieval, ranking, and evaluation while building and leading a team of engineers who implement the roadmap.

You will personally shape technical direction, mentor senior ICs, and collaborate with product and ML teams. This role blends hands-on leadership with strategic scope in a high-impact area.

Qualifications

  • 12+ years in ML or software with a focus on search systems.
  • Experience leading engineers, including hiring and mentorship.
  • Proven track record architecting large-scale search from design to production.
  • Deep understanding of information retrieval, ranking algorithms, and user modeling techniques.
  • Experience with offline evaluation and online A/B testing for relevance.

Responsibilities

  • Own architecture and long-term roadmap for large-scale, low-latency search infrastructure.
  • Lead and grow the search engineering team, mentoring senior ICs and engineers.
  • Set technical vision and drive hardest retrieval and ranking decisions while collaborating with leadership.
  • Implement safety guardrails for generative AI outputs and privacy-preserving techniques.

Skills

Search infra
Engineering leadership
Team mentorship
Architecture design
Hiring processes
Experimentation & A/B testing
Performance optimization

Education

MS in Computer Science or related field
PhD preferred

Tools

Milvus
Qdrant
Pinecone
FAISS
OpenSearch
Elasticsearch
Docker
Kubernetes
Kafka
Go
C++
Python
TensorFlow
PyTorch
Spark
Flink

Job description

We're building a massive, real-time search experience that sits at the intersection of Generative AI and Information Retrieval! We make sense of high-volume structured and multimodal data and complex behavioral signals which deliver results that feel instant and relevant while still being private. Join our team as a ML Search Engineering Manager and take part in this rare opportunity to shape a user-facing product that millions of Apple customers rely on every day!

DESCRIPTION

We are looking for a Search Engineering Manager & Lead to serve as both the senior technical authority and the people leader for our search team. You'll own the architecture and long-term technical roadmap for large-scale, low-latency search infrastructure, from query understanding and hybrid retrieval through ranking and evaluation, and you'll also build, grow, and lead the team of search engineers who bring that roadmap to life. This is a hands-on leadership role with dual scope: you set the technical vision and personally shape the hardest retrieval and ranking decisions, and you also manage, mentor, and grow the engineers executing against it. Your leverage comes equally from what you design and from the team you build.

MINIMUM QUALIFICATIONS
  • MS in Computer Science, Engineering, or a related technical field, or equivalent experience. PhD preferred.
  • 12+ years of experience in Machine Learning, Data Science, or Software Engineering, with a significant focus on search infrastructure and information retrieval, including at least 5 years operating in a technical leadership or engineering management capacity.
  • Proven experience leading and managing engineers, including hiring, performance management, and technical mentorship of senior and staff ICs.
  • Track record of leading the architecture of large-scale search systems from design through production.
  • Deep understanding of information retrieval, ranking algorithms, and user modeling techniques.
  • Experience designing offline evaluation frameworks and online A/B testing methodology to validate search relevance and ranking quality.
  • Experience with vector databases (Milvus, Qdrant, Pinecone, or FAISS).
  • Experience with search infrastructure such as OpenSearch, Elasticsearch, or similar stacks.
  • Experience with cloud environments (AWS or GCP), containerization (Docker, Kubernetes), and streaming platforms (Kafka or comparable brokers).
  • Excellent written and verbal communication, with the ability to align engineers, partner teams, and senior leadership around a shared technical direction.
  • Strong proficiency in a systems language such as Go or C++, with working proficiency in Java or Python.
  • Deep familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost, or similar) and ML system design, model lifecycle, and experimentation pipelines.
  • Extensive experience with large datasets, data processing pipelines (Spark, Flink), and scalable architectures.
  • Working knowledge of data privacy principles (e.g., data minimization, privacy-preserving techniques) and experience applying them to systems that use user behavioral signals.
  • Experience implementing safety guardrails for generative AI outputs, including hallucination mitigation, harmful-content filtering, and red-team or adversarial evaluation practices.
PREFERRED QUALIFICATIONS
  • Published work or patents in search systems, information retrieval, or related ML fields.
  • Strong foundation in deep learning architectures for search and retrieval (transformers, graph neural networks, learned sparse representations).
  • Exposure to multi-objective optimization in search (relevance, diversity, freshness, fairness).
  • Track record of scaling engineering teams and modernizing infrastructure with measurable cost and reliability improvements.
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