Senior Applied Scientist, Search & Information Retrieval

Accountabilities:

• Design, build, and deploy large-scale information retrieval systems with a focus on search relevance, ranking quality, and low-latency performance at scale.

• Own end-to-end development of NLP and IR models, including research, data preparation, training, evaluation, and production deployment.

• Develop robust evaluation frameworks covering offline and online metrics such as precision@K, recall@K, relevance scoring, and latency benchmarks.

• Translate complex business and customer needs into clear technical requirements, scoped solutions, and delivery milestones.

• Collaborate with engineering teams on MLOps pipelines, model monitoring, retraining workflows, and production reliability.

• Operate in an agile, iterative environment, using feedback loops to continuously refine models and system performance.

• Contribute to research outputs including publications and patentable innovations while supporting knowledge sharing across teams.

• Mentor junior scientists and contribute to technical leadership within applied research initiatives.

Requirements:

• PhD in Computer Science, Artificial Intelligence, NLP, Information Retrieval, or related field, or Master’s with equivalent industry experience.

• 5+ years of post-degree experience building and deploying production-grade IR and NLP systems (not purely academic/research experience).

• Strong publication record in top-tier venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, KDD).

• Strong programming skills in Python with hands-on experience in PyTorch and Hugging Face Transformers.

• Proven experience designing and operating large-scale search systems, including indexing, query optimization, and latency-sensitive retrieval.

• Deep understanding of evaluation methodologies for search/NLP systems, including offline and online experimentation frameworks.

• Ability to translate ambiguous, complex business problems into scalable machine learning solutions.

• Strong collaboration skills working with product, engineering, and cross-functional stakeholders in agile environments.

• Nice to have: experience with Elasticsearch or OpenSearch, cloud ML platforms (AWS SageMaker or AzureML), or legal-domain search/NLP.

Benefits:

• Competitive compensation package with base salary ranging from $100,000 CAD – $145,000 CAD (Ontario), plus potential annual bonus based on performance.

• Flexible work arrangements, including “work from anywhere” options for up to 8 weeks per year.

• Comprehensive health benefits including medical, dental, vision, life, and disability insurance.

• Strong retirement savings programs and employee stock purchase plan.

• Paid time off, company-wide mental health days, parental leave, and sabbatical opportunities.

• Continuous learning and career development programs focused on AI and future-ready skills.

• Employee wellness support including fitness reimbursement, mental health resources, and assistance programs.

• Inclusive, globally recognized workplace culture focused on flexibility, belonging, and professional growth.

• Social impact initiatives, including paid volunteer days and ESG-related engagement opportunities.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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