About Persistent
We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what?s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.
Our disruptors mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We reported $1,654.4M FY26 revenue with 17.4% Y-o-Y growth. We have delivered 24 sequential quarters of growth with $436.0M in Q4 FY26 revenue, up 3.2% Q-o-Q and 16.2% Y-o-Y growth. Our 27,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We have been recognized as the Fastest Growing IT Services Brand Globally in the 2026 Brand Finance IT Services 25 Report. We named a Leader in the Everest Group Private Equity (PE) Services PEAK Matrix Assessment 2026 and Software Product Engineering PEAK Matrix Assessment 2026.
About Position:
We are seeking a Computational Biologist / Structural Bioinformatics Scientist to serve as the scientific expert within the Bio-ML platform team. This role is responsible for ensuring that the platform is scientifically meaningful by selecting the right computational biology AI models for specific biological questions, validating deployed models for scientific correctness, designing end-to-end computational workflows, and translating complex biology requirements into actionable technical specifications for engineering teams.
- Role: Computational Biologist / Structural Bioinformatics Scientist
- Location: Gurugram
- Experience: 8-12 years
- Job Type: Full Time Employment
What You'll Do:
- Define which computational biology AI models (AlphaFold2, AlphaFold-Multimer, ProteinMPNN, Boltz, RFDiffusion, etc.) are needed for the platform and for which use cases
- Stay current with the structural biology AI literature (CASP, Nature Methods, bioRxiv) and evaluate new models for adoption
- Benchmark models against each other and against experimental data; provide go/no-go recommendations
- Define acceptable quality thresholds: pLDDT scores, PAE matrices, RMSD cutoffs, docking scores
- Advice on when to use AF2-Multimer vs ColabFold vs ESMFold based on input type and required accuracy
- Design end-to-end computational workflows: sequence retrieval ? MSA ? structure prediction ? downstream analysis
- Define the input/output contracts for each model in biological terms (FASTA, mmCIF, PDB, SDF, SMILES)
- Validate deployed NIM services against reference runs to confirm scientific correctness post-deployment
- Design regression test sets using benchmark proteins (CASP targets, PDB structures with known conformations)
- Evaluate and validate LigandMPNN outputs for protein-ligand interface design tasks
- Interpret Boltz-1 predictions for protein-nucleic acid and protein-small molecule complexes
Expertise You'll Bring:
- 3?8 years of experience, or PhD + 1?3 years postdoctoral experience
- M.Tech / PhD in Bioinformatics, Biochemistry, Structural Biology, Computational Chemistry, or related field
- Deep expertise in structural bioinformatics and computational biology
- Strong capability to validate scientific correctness of AI-driven bioinformatics models and workflows
- Deep hands-on experience with AlphaFold2, including:
- running predictions
- interpreting pLDDT, PAE, and TM-score
- Experience with AlphaFold-Multimer for protein complex prediction and understanding of interface confidence metrics
- Practical experience with ColabFold, ESMFold, or RoseTTAFold2 as comparison tools
- Knowledge of Boltz or AlphaFold3 for multi-molecular complex prediction
- Conceptual understanding of AlphaFold2 model architecture, including:
- Evoformer
- Practical experience with ProteinMPNN for protein sequence design around small molecule binding sites
- Understanding of ProteinMPNN (backbone-only) vs LigandMPNN (ligand-aware) and when to use each
- Familiarity with RFDiffusion for backbone hallucination and binder design
- Experience with ESM2 or ProteinMPNN for inverse folding tasks
Benefits:
- Competitive salary and benefits package
- Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
- Opportunity to work with cutting-edge technologies
- Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
- Annual health check-ups
- Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents
Values-Driven, People-Centric & Inclusive Work Environment:
Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.
- We support hybrid work and flexible hours to fit diverse lifestyles.
- Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.
- If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment
Let?s unleash your full potential at Persistent - persistent.com/careers
Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.
