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Remote Library & Information Science Jobs in California

Chemify Ltd

Staff CADD Scientist

San Francisco, CA · On-site +1

... library generation. This gives our computational scientists something rare: a direct, high ... San Francisco (hybrid) or fully remote from Boston / San Diego Travel: Regular travel to our ...

NextSense

Senior ML/Research Scientist

Mountain View, CA · On-site +1

$116K - $148K/yr

Engage in building tools, libraries, or processes that are used throughout the company or in the ... Experience with version control (e.g., Git) Additional Information Benefits: * Our careers benefits ...

Relativity

Principal Applied Scientist

Los Angeles, CA · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team sits at the core of Relativity's AI development. We ...

Waymo

Data Scientist

Mountain View, CA · On-site +1

$170K - $216K/yr

Autonomous driving presents a new paradigm in data science: in addition to leveraging data ... Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: * PhD in a ...

Waymo

Data Scientist

San Francisco, CA · On-site +1

$170K - $216K/yr

Autonomous driving presents a new paradigm in data science: in addition to leveraging data ... Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: * PhD in a ...

SAIC

IT Systems Administrator

Anaheim, CA · Remote

$80K - $120K/yr

Engineering and Sciences Subcategory: Systems Engineer Schedule: Full-Time Shift: Day Job Travel ... None Potential for Remote Work: ORA_HYBRID Description SAIC is hiring for a Systems Administrator ...

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How much do remote library & information science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for remote library & information science in California is $64,339.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,800.00 and $74,000.00 per year, depending on experience, location, and employer.

What is a Remote Library & Information Science job?

A Remote Library & Information Science job involves managing, organizing, and providing access to information resources in a digital or virtual environment. Professionals in this field work remotely to support libraries, archives, research institutions, or corporations by cataloging materials, conducting research, and assisting users with information retrieval. They may also manage digital repositories, develop metadata standards, or provide virtual reference services. These roles require strong information management skills, proficiency in digital tools, and the ability to work independently.

What are the key skills and qualifications needed to thrive in the Remote Library & Information Science position, and why are they important?

To thrive in a Remote Library & Information Science role, you should have a strong background in information management, research, organization, and librarianship, usually supported by an MLS/MLIS degree. Familiarity with library management systems (e.g., Koha, Alma), digital resource platforms, and online databases is often required, and certifications such as Certified Information Professional (CIP) can be advantageous. Strong communication, self-motivation, and problem-solving skills help you excel in a remote environment and collaborate virtually with teams or patrons. These abilities ensure efficient information delivery, support user needs, and maintain high service standards despite working remotely.

What does a typical workday look like for someone in a Remote Library & Information Science position?

A typical workday in a remote library and information science role often involves managing digital collections, responding to research inquiries, cataloging resources, and providing virtual reference or support services to users. You may attend virtual meetings, collaborate with academic or organizational teams, and participate in online training or professional development. Communication is typically conducted via email, chat, or video conferencing platforms, and a large portion of your tasks are completed independently with periodic check-ins. Balancing multiple projects and maintaining strong organization skills is key to succeeding in this flexible, digitally-driven environment.

What are popular job titles related to Remote Library & Information Science jobs in California? For Remote Library & Information Science jobs in California, the most frequently searched job titles are:
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Remote Library Information Science jobs near you
Infographic showing various Remote Library & Information Science job openings in California as of June 2026, with employment types broken down into 4% Internship, 67% Full Time, 20% Part Time, 2% Temporary, and 7% Contract. Highlights an 100% Remote job distribution, with an average salary of $64,339 per year, or $30.9 per hour.

Staff CADD Scientist

Chemify Ltd

San Francisco, CA • On-site, Remote

Full-time

Posted 26 days ago

Job description

About Chemify:
Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world's largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity.
Our Chemifarm facility in Glasgow operates a growing fleet of advanced robotic systems that automate synthesis, optimisation, and library generation. This gives our computational scientists something rare: a direct, high-throughput bridge from in silico design to physically synthesised molecules, closing the design-make-test loop at a pace conventional drug discovery organisations cannot match.
Location: San Francisco (hybrid) or fully remote from Boston / San Diego
Travel: Regular travel to our Glasgow HQ / Chemifarm
The Role
We are seeking a Staff CADD Scientist to drive computer-aided drug design on Chemify's commercial programmes and computational platform. You will sit at the centre of a cross-disciplinary team - computational chemists, in-house and partner medicinal chemists, AI researchers, data engineers, and automation scientists - and shape how structure, simulation, and machine learning translate into molecules we actually make.
Your work sits at the interface between Chemify's platform and our commercial partners' drug discovery programmes. You will design and prioritise molecules for synthesis, work directly with partner chemists on medicinal-chemistry strategy - turning computational proposals into physically-made compounds.
If you are energised by solving complex scientific problems at the intersection of chemistry, physics, and AI - and by seeing your designs synthesised and tested within days rather than months - we'd love to welcome you to our team.
Key Responsibilities
  • Own the computational design approach on assigned programmes, from hit discovery through lead optimisation; partner with in-house and customer chemists on MPO and translate SAR into actionable hypotheses across DMTL cycles.
  • Deploy and advance methods across the CADD stack - docking, pharmacophore, shape and 3D-similarity, MD, FEP, QSAR modelling - choosing the right blend of physics- and ML-based approaches for each programmes.
  • Communicate reasoning, trade-offs, and recommendations to partner chemists and project leads.
  • Help productionise CADD methods into a reproducible, API-first toolkit; partner with Infrastructure on cost-effective GPU/HPC workflows.
  • Mentor computational chemists and junior CADD scientists; partner with the Head of Advanced Machine Learning on hiring and growth; act as the scientific interface with customers on commercial projects.
  • Represent Chemify's CADD capability externally - publications, conferences, and partner engagements where appropriate.

About You
You are a rare hybrid: a deeply credible computational chemist who is equally comfortable reasoning protein-ligand interactions and shipping code that runs in production. You care about getting real molecules made, not only writing elegant methods.
We expect you to bring:
  • PhD (or equivalent experience) in Computational Chemistry, Structural Biology, Biophysics, Physics, or a closely related field, plus 8+ years of hands-on CADD experience in small-molecule drug discovery - including owning the computational strategy on active programmes.
  • Strong grounding in both structure- and ligand-based drug design - protein-ligand biophysics on one side, and pharmacophore, shape, and SAR-driven design on the other - with hands-on use of standard CADD stack (e.g. MOE, PyMOL, OpenMM / GROMACS / AMBER).
  • Familiarity with core drug discovery and medicinal chemistry principles - translating diverse assay readouts into design hypotheses - and a clear understanding of pharmacological principles to keep CADD output biologically relevant.
  • Working knowledge of modern deep learning for molecular design (GNNs, generative models, property prediction), and a clear sense of when these complement traditional CADD methods rather than replace them.
  • Strong Python and at least one core cheminformatics toolkit (e.g. RDKit, OpenEye); real experience inside the drug-discovery loop (SAR, MPO, DMTL cycles, lead optimisation, library enumeration); comfort with GPU-accelerated simulation and cloud/HPC workflows.
  • The ability to present computational reasoning to working chemists and partner scientists and a track record of technical leadership beyond your own projects.

Beneficial Skills
  • Hands-on experience with free energy perturbation (FEP+, OpenFE, or equivalent) in a production drug-discovery setting.
  • Practical use of generative chemistry methods (diffusion, autoregressive, RL-based design), including a clear-eyed view of their failure modes.
  • Familiarity with active learning, iterative DMTL design loops, and Bayesian optimisation applied to molecular design.
  • Experience building or integrating CADD tooling into API-first platforms (FastAPI, Docker, CI/CD), and proficiency in C/C++ / CUDA for high-performance computational chemistry.
  • A visible track record in the field - peer-reviewed publications, open-source contributions, or public projects that demonstrate your judgement on real CADD problems.

Why Join Chemify?
Impact:
You will directly shape the molecules Chemify designs and makes - at a company uniquely positioned to close the design-make-test loop through automated chemical synthesis at scale.
Autonomy:
Reporting to the Head of Advanced Machine Learning, you will own CADD strategy on your programmes, choose the methods and tools, and have meaningful influence over the computational platform that supports every project at Chemify.
Ambition:
We are a Series B deep-tech company investing in world-class infrastructure and tackling problems at the frontier of AI, robotics, and chemistry. You will have the resources, the data, and the mandate to do CADD in a way that isn't possible elsewhere.

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