Seeking a Senior Linux DevOps Engineer for an on-site, 6-12 month contract-to-hire engagement in Vancouver, British Columbia, Canada. This senior-level role supports high-performance computing (HPC) and electronic design automation (EDA) infrastructure within a data center organization.
Responsibilities
Support and administer SLURM-based HPC compute environments, including partition configuration and migration planning
Plan and execute HPC and EDA compute and storage infrastructure migrations across data centers
Develop migration strategies and evaluate implementation options, risks, dependencies, and operational trade-offs
Create formal Method of Procedure (MOP) documents and runbooks for infrastructure changes and service cutovers
Coordinate with EDA, storage, and identity and access management teams to deliver platform changes
This role builds and applies molecular-scale modeling within DDCS, independently designing and executing simulations to explain and predict how drug molecules, excipients, and delivery vehicles behave.
Compensation
The anticipated wage for this position is $168,000 - $246,400
Responsibilities
Independently design, execute, and interpret all-atom molecular dynamics, coarse-grained, and mesoscale simulations to answer defined formulation and delivery questions across early- and late-phase programs.
Apply enhanced-sampling and free-energy methods — umbrella sampling, metadynamics, free-energy perturbation, thermodynamic integration — where unbiased equilibrium sampling cannot reach the relevant states.
Assign and justify protonation states for titratable groups as a routine condition of simulation setup, and apply constant-pH molecular dynamics or continuum electrostatics where charge state is itself the question.
Compute thermophysical and rheological properties from simulation and report them with statistical uncertainty and an explicit domain of validity in concentration, temperature, and shear regime.
Apply electronic-structure and semi-empirical methods (e.g., DFT, xTB) to derive partial charges, torsional parameters, and conformer energetics where empirical force-field parameters are missing or unreliable for a given chemistry.
Requirements
Master's degree in computational chemistry, chemical physics, chemical engineering, materials science, biophysics, physics, or a related field
Lead the engineering organization for FAR.AI’s Frontier Safety division, building scalable tools, systems, and teams to support high‑stakes AI safety testing and research.
Compensation
Compensation: $225,000-$350,000/year depending on experience and location, with the potential for additional compensation for exceptional candidates.
Responsibilities
Build and scale a technical engine for red‑teaming, evaluations, and safeguards.
Develop and maintain tooling, products, services, and agentic systems.
Operationalize and scale systems for attacker simulation and severity evaluation.
Maintain internal vulnerability databases, statistical analysis tools, and reporting infrastructure.
Design sandboxing architecture for rapid evaluation of AI systems.
Design, develop and deploy quantitative tools supporting trading and research, including pricing, backtesting, risk analysis and PnL reporting.
Responsibilities
Design, develop and deploy quantitative tools supporting trading and research, including pricing, backtesting, risk analysis and PnL reporting
Build Python applications and data pipelines to explore, integrate and analyse alternative datasets, including weather and cargo data
Collaborate with Quantitative Researchers and Traders to translate trading ideas and business requirements into production applications and quantitative models
Architect, develop and maintain cloud applications in collaboration with infrastructure engineers, using AWS and related technologies
Develop and apply statistical and machine learning models to support research and trading across Agriculture, Metals and Energy
Analyst/Consultant focused on AI, HPC, and quantum computing solutions for Life Sciences.
Responsibilities
Translate business challenges into applied AI and HPC solutions, from conceptualization to proof of concept and pilot
Design, prototype, and validate end-to-end use cases, prioritizing usable outcomes and short iteration cycles
Adapt and evaluate emerging models and frameworks (GenAI, foundation models, GPU acceleration) to each client's context and constraints
Take part in the full project lifecycle: problem analysis, solution design, implementation, and communication of results
Collaborate with multidisciplinary teams (client, business, data engineering, domain scientists), translating complex technical work into actionable recommendations
Requirements
Bachelor's or Master's in Physics, Mathematics, Computer Science, Bioinformatics, or an equivalent quantitative discipline
Annapurna Labs is looking for an experienced Engineering Manager to think big in defining the strategic direction, roadmap, and execution for EDA infrastructure supporting SoC, IP, physical design, and verification teams.
Compensation
USA, TX, Austin - 184,900.00 - 250,200.00 USD annually
Responsibilities
Build, inspire, and develop a high-performing, globally distributed team of 6–10 software development engineers and systems engineers; set clear expectations, conduct regular performance reviews, and foster a culture of ownership, operational excellence, and customer obsession.
Recruit, hire, and retain top engineering talent; own the hiring bar for your team and actively build a diverse pipeline of candidates who strengthen the organization.
Coach and develop engineers at all levels; create individualized growth plans, identify future leaders, and invest in the career development of every team member to build the next generation of engineering leaders.
Define the team’s vision, strategy, and multi-year roadmap for EDA infrastructure; align priorities with organizational goals and communicate the strategy clearly to stakeholders at all levels.
Define and track success metrics for the team and the services it provides, using data-driven dashboards and AI-assisted analytics to inform priorities, measure impact, and hold the team accountable to results.
Requirements
Bachelor's degree or above in computer science, electrical engineering, or related field
Provide application and infrastructure support for Viridien HPC and software solutions to external clients, including onsite installation, remote troubleshooting, and automation.
Responsibilities
Install, configure, and validate Viridien software and HPC solutions, including onsite installation and integration for external clients' on-prem environments, as well as Viridien SaaS platform solutions.
Support the day-to-day monitoring, troubleshooting and resolution of support tickets, providing remote application support and HPC assistance to external clients.
Participate in Viridien software release building and validation.
Engage with clients to understand their technical requirements and propose suitable Linux & HPC solutions.
Create and maintain clear technical documentation, knowledge articles, operating procedures and handover notes.
Requirements
Bachelor's degree in Computer Science, Computer Engineering, Computer Information Systems or related computing subjects
Nice to have: Experience with HPC hardware installation and maintenance
Nice to have: Experience with job scheduling solutions (Slurm, PBSPro)
Nice to have: Knowledge of database installation and administration
Nice to have: Knowledge of Puppet, GitLab, OpenStack, Kickstart, Kubernetes, CI/CD, Zabbix
Build and maintain the AI infrastructure that powers scientific discovery at Biohub.
Compensation
The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is for Senior Machine Learning Engineer $214,000 -$268,000 and for Staff Machine Learning Engineer $241,000 - $301,000 annually. Final compensation is based on the level at which you are hired. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
Responsibilities
Work with researchers to train, fine-tune, and evaluate biological foundation models and diagnose training problems.
Help evaluate and curate training and validation datasets at Petabytes scale.
Design and create libraries and abstractions that researchers and engineers build on.
Optimize GPU-native data loading for large tensor workloads and resolve hardware utilization bottlenecks across backends.
Build and maintain reliable distributed pre and post training systems.
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
Computational Scientist – Molecular Modeling & SimulationNewLilly · Indianapolis, US
Head of Engineering (Frontier Safety)NewFAR.AI · Remote
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Machine Learning Engineer, AINewBiohub · Redwood City, US