Senior MLOps Engineer Toronto, Ontario Engineering / Full-time / Hybrid About Us Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created. Opportunity Join us in building the future of AI-driven drug discovery as a Senior MLOps Engineer. You will own and evolve the infrastructure that powers our ML pipelines – from cloud environments and CI/CD systems to workflow orchestration and model deployment. You will work closely with ML scientists, bioinformaticians, and software engineers to keep our platform reliable, reproducible, and scalable. Ideal Candidate You are someone who enjoys keeping the infrastructure running smoothly so that scientists can focus on their research. You are comfortable working across cloud platforms, CI/CD systems, containers, and GPUs – and you take pride in making these systems reliable and easy for others to use. You have 4+ years of experience in production infrastructure or MLOps, you write solid Python, and you are curious about the ML and scientific workflows your work supports. Above all, you are a collaborative, kind team member who communicates clearly, adapts to evolving needs, and is happy to help colleagues grow their own infrastructure skills along the way. If this sounds like you, we would love to hear from you. Key Responsibilities - Maintain and improve cloud infrastructure (GCP) using Infrastructure-as-Code tools (Terraform). - Manage IAM, RBAC, and permission policies across cloud environments. - Own and evolve CI/CD pipelines (CircleCI, GitHub Actions) and ensure best practices are followed across the engineering and ML teams. - Administer and support workflow orchestration platforms (e.g., Seqera/Nextflow, Argo, Kubeflow). - Operate and configure ML experiment tracking and registry tooling (e.g., W&B, MLflow). - Build and maintain containerized environments (Docker) and manage Kubernetes clusters. - Manage GPU resources – provisioning, scheduling, and debugging hardware and driver issues. - Write and maintain Python tooling, scripts, and integrations that support ML infrastructure. - Help deploy ML models to production environments and monitor their performance. Basic Qualifications - 4+ years of experience operating production infrastructure. - Proficiency with cloud platforms (GCP preferred; AWS/Azure acceptable) and Infrastructure-as-Code (Terraform). - Extensive Hands-on experience with Kubernetes and containerization (Docker). - Solid background in CI/CD systems (CircleCI, GitHub Actions, or similar). - Experience managing GPU compute (provisioning, debugging, driver management). - Familiarity with Python package and environment management (e.g., pip, conda, pixi). - Strong Python programming skills. - Self-motivated problem solver with excellent communication skills. Preferred Qualifications - Understanding of ML frameworks (e.g., PyTorch, PyTorch Lightning), ML workflows (training, inference, evaluation), and the model lifecycle. - Familiarity with MLOps tooling (e.g., W&B, Ray, VertexAI) and distributed compute patterns (e.g., DDP, realtime/batch inference, multi-node training). - Familiarity with Kubernetes CRDs and batch/gang schedulers (e.g., Volcano, Kueue). - Experience working with large-scale datasets (storage, versioning, efficient access patterns). - Experience working directly with scientists and researchers in an interdisciplinary setting. - Knowledge of biology and/or machine learning science. - Familiarity with data compliance and governance frameworks (e.g., HIPAA, SOC 2). - Previous startup experience. What We Offer - A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery. - Highly competitive compensation, including meaningful stock ownership. - Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program. - Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days. - Maternity and parental leave top-up coverage, as well as new parent paid time off. - Focus on learning and growth for all employees - learning and development budget & lunch and learns. - Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences. Deep Genomics encourages applications from all backgrounds who seek the opportunity to build the world's leading AI-driven genetic medicine company. If you have a disability or special need, accommodation is available on request for candidates taking part in all aspects of the selection process. *This posting reflects a current vacancy. We offer competitive compensation aligned with local market benchmarks. The salary range for this role is $175,000 - $200,000, and reflects Canada-based roles; compensation may differ for U.S.-based candidates.

• Invent and productionize Transformer/RAG/Graph RAG architectures that surface the right contact, company, or insight while driving quantization, distillation, and SLM fine-tuning (GTE-Qwen, modernBERT) so models stay fast and affordable at petabyte scale • Prototype and launch hybrid dense/sparse retrieval pipelines on vector DBs to build language-agnostic clustering and classification systems that power our intelligence layer • Own high-recall NER models that tag people, orgs, locations, and industry-specific entities across multi-language text, extracting structured insights from web data to improve our signal detection capabilities • Build cross-dataset entity-resolution frameworks that dedupe and merge hundreds of millions of fragmented company and person records with sub-second latency, creating enriched, unified entities enhanced with knowledge-graph signals • Design and implement agentic workflows with robust evaluation frameworks focused on NER and entity resolution tasks, including large-scale A/B and back-testing plans that close the loop from experiment to KPI uplift • Scale ML solutions and drive cross-functional impact by partnering with ML engineers to ensure production reliability, translating product goals into measurable ML KPIs, and influencing roadmap and investment decisions while mentoring junior scientists and engineers • Drive end-to-end project ownership from problem definition through deployment, collaborating closely with engineering and product teams to understand business requirements and translate them into scalable ML solutions that enhance foundation data quality across company firmographics, professional demographics, C-suite profiles, and web-extracted signals

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams - People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more - provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block. The Role The Credit and Lending team is responsible for the predictive intelligence that underpins Block's primary capital-intensive products. These products unlock unique access to credit for our customers, many of whom are otherwise underbanked and underserved by the traditional financial system. As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems. This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block's top-line growth. Our credit products are material drivers of the company's profitability and are frequently highlighted in executive reviews and quarterly earnings reports. We are seeking a scientifically-minded contributor capable of delivering extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques. You Will - Apply a rigorous scientific mindset to the challenge of underwriting new customer segments, involving the evaluation of alternative external data sources and the deployment of advanced architectures to enhance predictive accuracy. - Lead complex ML Operations and Infrastructure initiatives that advance our modeling capabilities, such as scaling data ingestion or enabling the use of more complex neural networks. - Design and implement the full credit modeling stack, taking responsibility for the entire lifecycle of credit decisioning and ensuring models are robustly integrated into production environments. - Use data science techniques to leverage new data sources for modeling, making sense of messy datasets and bringing clarity to business decisions. - Identify and execute material improvements to credit policy, applying an analytical lens to determine where technical or logic shifts can yield significant positive outcomes for the customer and the bank's portfolio. - Support team members in ad-hoc and scheduled updates to existing models, and help troubleshoot issues in a real-time production environment. - Operate effectively within the framework of a regulated bank (SFS), balancing rapid innovation with the requirements of safety, soundness, and compliance. You Have - Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience, with a focus on developing and deploying machine learning and statistical models in production environments. - A degree in a technical field (e.g., Computer Science, Mathematics, Statistics, Physics, or Engineering). We have a strong preference for candidates with a demonstrated track record of scientific research or an advanced degree. - Strong quantitative intuition and data visualization skills, with a proven ability to conduct sophisticated ad-hoc and exploratory analysis. - Full-stack proficiency preferred, including the ability to contribute across the entire technical stack-from data pipelines to production-grade software architecture. - The versatility to communicate clearly with both technical and non-technical audiences, particularly in the context of high-visibility projects and executive stakeholders. - A pragmatic approach to problem-solving, with a willingness to utilize whichever tool is most appropriate for the situation while balancing complex business, technical, and regulatory constraints. - Experience with tree-based models and gradient boosting is helpful but not required; we value the ability to adapt and learn new methodologies as the credit landscape evolves. We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page . Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future. To find a location's zone designation, please refer to this resource . If a location of interest is not listed, please speak with a recruiter for additional information. Zone A: $228,700 - $343,100 USD Zone B: $217,300 - $325,900 USD Zone C: $205,900 - $308,900 USD Zone D: $194,500 - $291,700 USD Application Guidelines Candidates may submit up to 9 active applications within a 60-day period. Reapplications to the same role are accepted 90 days after a previous application has been reviewed. Use of AI in Our Hiring Process We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws. Contact us here with hiring practice or data usage questions. Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block. Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we're helping build a financial system that is open to everyone.

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams - People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more - provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block. The Role The Credit and Lending team is responsible for the predictive intelligence that underpins Block's primary capital-intensive products. These products unlock unique access to credit for our customers, many of whom are otherwise underbanked and underserved by the traditional financial system. As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems. This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block's top-line growth. Our credit products are material drivers of the company's profitability and are frequently highlighted in executive reviews and quarterly earnings reports. We are seeking a scientifically-minded contributor capable of delivering extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques. You Will - Apply a rigorous scientific mindset to the challenge of underwriting new customer segments, involving the evaluation of alternative external data sources and the deployment of advanced architectures to enhance predictive accuracy. - Lead complex ML Operations and Infrastructure initiatives that advance our modeling capabilities, such as scaling data ingestion or enabling the use of more complex neural networks. - Design and implement the full credit modeling stack, taking responsibility for the entire lifecycle of credit decisioning and ensuring models are robustly integrated into production environments. - Use data science techniques to leverage new data sources for modeling, making sense of messy datasets and bringing clarity to business decisions. - Identify and execute material improvements to credit policy, applying an analytical lens to determine where technical or logic shifts can yield significant positive outcomes for the customer and the bank's portfolio. - Support team members in ad-hoc and scheduled updates to existing models, and help troubleshoot issues in a real-time production environment. - Operate effectively within the framework of a regulated bank (SFS), balancing rapid innovation with the requirements of safety, soundness, and compliance. You Have - Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience, with a focus on developing and deploying machine learning and statistical models in production environments. - A degree in a technical field (e.g., Computer Science, Mathematics, Statistics, Physics, or Engineering). We have a strong preference for candidates with a demonstrated track record of scientific research or an advanced degree. - Strong quantitative intuition and data visualization skills, with a proven ability to conduct sophisticated ad-hoc and exploratory analysis. - Full-stack proficiency preferred, including the ability to contribute across the entire technical stack-from data pipelines to production-grade software architecture. - The versatility to communicate clearly with both technical and non-technical audiences, particularly in the context of high-visibility projects and executive stakeholders. - A pragmatic approach to problem-solving, with a willingness to utilize whichever tool is most appropriate for the situation while balancing complex business, technical, and regulatory constraints. - Experience with tree-based models and gradient boosting is helpful but not required; we value the ability to adapt and learn new methodologies as the credit landscape evolves. We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page . Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future. To find a location's zone designation, please refer to this resource . If a location of interest is not listed, please speak with a recruiter for additional information. Zone A: $228,700 - $343,100 USD Zone B: $217,300 - $325,900 USD Zone C: $205,900 - $308,900 USD Zone D: $194,500 - $291,700 USD Application Guidelines Candidates may submit up to 9 active applications within a 60-day period. Reapplications to the same role are accepted 90 days after a previous application has been reviewed. Use of AI in Our Hiring Process We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws. Contact us here with hiring practice or data usage questions. Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block. Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we're helping build a financial system that is open to everyone.