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Role: Protein Engineering Scientist (AI-Driven Large Molecule Design) Location: Science & Technology Park / Venture Center, Pune, Maharashtra Work Mode: Hybrid/Remote- 6 days Role Overview We are looking for a Protein Engineering Scientist with strong hands-on experience in computational protein design and large molecule engineering. This role focuses on: ● protein and enzyme engineering ● antibody and binder design ● AI-driven structure and sequence generation ● end-to-end large molecule design workflows You will work at the intersection of biology, AI, and computational modeling to design and optimize next-generation protein therapeutics and engineered biomolecules. What You’ll Work On ● Designing and optimizing proteins, enzymes, antibodies, and other large molecules for specific functional outcomes ● Working on end-to-end protein engineering workflows from sequence to structure to function ● Applying AI-driven approaches for protein structure prediction and design ● Designing mutations to improve stability, binding affinity, specificity, and activity ● Analyzing protein-protein and protein-ligand interactions ● Integrating generative AI models into protein and enzyme engineering pipelines ● Working with evolving toolchains and adapting to new methods in AI-driven protein design ● Collaborating with cross-functional teams across computational and experimental domains Key Responsibilities ● Execute protein engineering workflows including sequence design, structure prediction, and optimization ● Work with advanced AI-driven tools such as RFdiffusion, AlphaFold 3, ProteinMPNN, and Boltz-2 ● Leverage additional emerging tools and frameworks in protein and large molecule design as required ● Design and evaluate enzyme variants and antibody candidates for therapeutic and industrial applications ● Analyze structural outputs to assess stability, folding, and binding interactions ● Develop and refine computational pipelines for large molecule and protein engineering ● Collaborate with AI/ML and backend teams to integrate protein design workflows into scalable systems ● Interpret computational outputs and translate them into actionable biological insights Tech Stack ● Protein & Large Molecule Design: RFdiffusion, AlphaFold 3, ProteinMPNN, Boltz-2, and other emerging tools ● Molecular Modeling: PyMOL, Chimera, docking and structural analysis tools ● Simulation (Preferred): MD tools such as GROMACS, OpenMM ● Programming: Python (NumPy, Biopython, PyTorch preferred) ● Other: Sequence analysis tools, structural biology toolkits What We’re Looking For Core Domain Expertise ● Strong understanding of protein engineering and large molecule design workflows ● Hands-on experience in enzyme engineering, antibody design, or protein therapeutics ● Deep understanding of protein structure-function relationships ● Familiarity with stability, folding, and interaction analysis AI-Driven Protein Design (Critical) ● Hands-on experience with modern AI-based protein design tools such as RFdiffusion, AlphaFold 3, MPNN-based methods, and related systems ● Understanding of generative approaches for protein structure and sequence design ● Ability to work with evolving AI toolchains in protein engineering Computational & Technical Skills ● Proficiency in Python for scientific computing ● Experience with structural biology and molecular modeling tools ● Ability to work with computational pipelines and large biological datasets Nice to Have ● Experience with molecular dynamics simulations ● Exposure to wet-lab validation workflows or experimental collaboration ● Experience in therapeutic protein or enzyme optimization pipelines ● Experience working in interdisciplinary AI + biology environments Eligibility: ● Master’s or PhD in Biotechnology, Bioinformatics, Computational Biology, Structural Biology, or related field ● 1–5 years of hands-on experience in protein engineering / enzyme engineering / antibody design Note: Exceptional candidates with strong project work or research experience in protein engineering and AI-driven design will also be considered.