Medvolt- Protein Engineer
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.
