Staff Engineer, Semantic Search & IR

Cohere; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Lunch stipend

Health and dental benefits

401K plan

Pension scheme

Parental leave top-up

Education stipend

6 weeks vacation

Travel budget to other offices

Home office stipend

Co-working benefit

Job summary

Cohere is seeking a Member of Technical Staff, Search to advance semantic search and information retrieval. You will design and train cutting-edge models, build data pipelines, and partner with model serving and product teams to deploy fast, accurate search solutions.

The role offers opportunities to publish work, collaborate with academic partners, and participate in a remote-friendly, hybrid environment across our New York office and other locations.

Qualifications

• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, TF-Serving, JAX, XLA/MLIR).
• Familiarity with training and using information retrieval models.
• Experience leveraging Large Language Models in training data or evaluation pipelines.
• Strong communication and problem-solving skills.

Responsibilities

• Design, train and improve upon cutting-edge search models.
• Gather high-quality retrieval datasets and optimize data pipelines for model training and evaluation.
• Work closely with the model serving team to ensure inference is fast and stable.
• Collaborate with product teams to develop solutions.
• Engage in research collaborations with partner organizations and publish work in top-tier conferences and journals.
• Join us at a pivotal moment, shape what we build, have an ownership mindset, and wear multiple hats!

Skills

Python

PyTorch

TensorFlow

JAX

TF-Serving

XLA/MLIR

Job description

Cohere is seeking a Member of Technical Staff, Search to advance semantic search and information retrieval. You will design and train cutting-edge models, build data pipelines, and partner with model serving and product teams to deploy fast, accurate search solutions.

The role offers opportunities to publish work, collaborate with academic partners, and participate in a remote-friendly, hybrid environment across our New York office and other locations.