63 Design Lead jobs in Delhi

Responsibilities :

• You should be a verification engineer with a knowledge of SoC integration verification, SoC scenario verification, SoC performance verification, CHI/PCIe/CXL, DDRx/LPDDRx integration verification in SoC RTL.
• Project experience with ARM based ecosystem components (A-series ARM Cores, SMMU, GIC, Core sight, NIC and other complex bus interconnects )
• Your key responsibilities will include writing test plans, defining test methodologies, developing SystemVerilog/Verilog testbenches and tests, and debugging of test failures and issues.
• Working with project management and leads on planning tasks, setting schedules, and quality checkpoints.
• Collaborate with engineers from design & performance analysis

Required Skills and Experience :

• Proven understanding of digital hardware design and Verilog/System Verilog HDL
• Experienced in one or more of various verification methodologies – UVM/OVM, formal, power aware verification, emulation
• Exposure to all stages of verification: requirements collection, creation of verification methodology plans, test plans, testbench implementation, test case development, documentation, and support
• Good Problem Solving and Debugging skills.

“Nice To Have” Skills and Experience :

• Knowledge of SoC Verification Flow and strategy.
• Experience with ARM-based designs and/or ARM System Architectures.

Responsibilities :

• You should be a verification engineer with a knowledge of SoC integration verification, SoC scenario verification, SoC performance verification, CHI/PCIe/CXL, DDRx/LPDDRx integration verification in SoC RTL.
• Project experience with ARM based ecosystem components (A-series ARM Cores, SMMU, GIC, Core sight, NIC and other complex bus interconnects )
• Your key responsibilities will include writing test plans, defining test methodologies, developing SystemVerilog/Verilog testbenches and tests, and debugging of test failures and issues.
• Working with project management and leads on planning tasks, setting schedules, and quality checkpoints.
• Collaborate with engineers from design & performance analysis

Required Skills and Experience :

• Proven understanding of digital hardware design and Verilog/System Verilog HDL
• Experienced in one or more of various verification methodologies – UVM/OVM, formal, power aware verification, emulation
• Exposure to all stages of verification: requirements collection, creation of verification methodology plans, test plans, testbench implementation, test case development, documentation, and support
• Good Problem Solving and Debugging skills.

“Nice To Have” Skills and Experience :

• Knowledge of SoC Verification Flow and strategy.
• Experience with ARM-based designs and/or ARM System Architectures.

About the Role

Pattern is building a next-generation AI-driven drug discovery platform that integrates state-of-the-art structural modeling, generative design, and reinforcement learning agents to explore the vast chemical space for novel small-molecule therapeutics.

We are seeking a Ligand Design & Pose Prediction Lead to guide de novo small-molecule exploration, interpret protein–ligand binding predictions, and prioritize compounds for synthesis/testing. You will work in close partnership with a deep learning specialist to combine cutting-edge AI tools with your medicinal chemistry and structure-based design expertise.

This is a strategic, non-lab role — your primary focus will be to bridge AI outputs with biological and chemical insight, ensuring the most promising designs move forward.

Key Responsibilities

Lead ligand pose prediction workflows using state-of-the-art AI and computational docking tools (e.g., DiffDock, EquiBind, Glide, GOLD).

Evaluate protein–ligand binding interactions for fit, contact quality, and structural plausibility.

Collaborate with AI/deep learning engineers to refine de novo molecular generation strategies using models such as REINVENT, Pocket2Mol, and diffusion-based 3D generators.

Apply drug-likeness, ADMET, novelty, and selectivity criteria to prioritize compound candidates.

Integrate binding mode insights with biological context from Pattern’s Agentix Knowledge Graph to align compounds with target mechanism-of-action.

Generate clear, actionable compound selection lists for partner synthesis and in-vitro testing.

Contribute to feedback loops by incorporating experimental assay data into ongoing model optimization.

Present binding hypotheses, SAR rationale, and prioritization strategies to cross-functional teams.

Qualifications Required

PhD or Masters in Medicinal Chemistry, Chemical Biology, Computational Chemistry, or related discipline (or MSc + 3+ years of relevant experience).

Proven experience in structure-based drug design and ligand pose evaluation.

Strong working knowledge of protein–ligand binding principles (H-bonds, hydrophobic contacts, electrostatics, shape complementarity).

Familiarity with AI/ML-based molecular design platforms.

Ability to work with predicted protein structures (AlphaFold/OpenFold) and assess binding pockets.

Experience applying drug-likeness rules and property-based filtering in lead prioritization.

Excellent communication skills and ability to work cross-functionally with AI engineers, biologists, and medicinal chemists.

Preferred

Familiarity with pharmacophore modeling and pocket geometry analysis.

Experience in multi-objective optimization (binding, ADMET, novelty).

Exposure to reinforcement learning-driven compound optimization workflows.

Why Join Us?

You’ll be joining at the frontier of AI-guided drug discovery, working side-by-side with deep learning experts to build a platform capable of efficiently searching through 10^60 chemical possibilities. Your expertise will directly shape the quality and novelty of our candidate compounds, accelerating the path from target to therapy.

About the Role

Pattern is building a next-generation AI-driven drug discovery platform that integrates state-of-the-art structural modeling, generative design, and reinforcement learning agents to explore the vast chemical space for novel small-molecule therapeutics.

We are seeking a Ligand Design & Pose Prediction Lead to guide de novo small-molecule exploration, interpret protein–ligand binding predictions, and prioritize compounds for synthesis/testing. You will work in close partnership with a deep learning specialist to combine cutting-edge AI tools with your medicinal chemistry and structure-based design expertise.

This is a strategic, non-lab role — your primary focus will be to bridge AI outputs with biological and chemical insight, ensuring the most promising designs move forward.

Key Responsibilities

Lead ligand pose prediction workflows using state-of-the-art AI and computational docking tools (e.g., DiffDock, EquiBind, Glide, GOLD).

Evaluate protein–ligand binding interactions for fit, contact quality, and structural plausibility.

Collaborate with AI/deep learning engineers to refine de novo molecular generation strategies using models such as REINVENT, Pocket2Mol, and diffusion-based 3D generators.

Apply drug-likeness, ADMET, novelty, and selectivity criteria to prioritize compound candidates.

Integrate binding mode insights with biological context from Pattern’s Agentix Knowledge Graph to align compounds with target mechanism-of-action.

Generate clear, actionable compound selection lists for partner synthesis and in-vitro testing.

Contribute to feedback loops by incorporating experimental assay data into ongoing model optimization.

Present binding hypotheses, SAR rationale, and prioritization strategies to cross-functional teams.

Qualifications Required

PhD or Masters in Medicinal Chemistry, Chemical Biology, Computational Chemistry, or related discipline (or MSc + 3+ years of relevant experience).

Proven experience in structure-based drug design and ligand pose evaluation.

Strong working knowledge of protein–ligand binding principles (H-bonds, hydrophobic contacts, electrostatics, shape complementarity).

Familiarity with AI/ML-based molecular design platforms.

Ability to work with predicted protein structures (AlphaFold/OpenFold) and assess binding pockets.

Experience applying drug-likeness rules and property-based filtering in lead prioritization.

Excellent communication skills and ability to work cross-functionally with AI engineers, biologists, and medicinal chemists.

Preferred

Familiarity with pharmacophore modeling and pocket geometry analysis.

Experience in multi-objective optimization (binding, ADMET, novelty).

Exposure to reinforcement learning-driven compound optimization workflows.

Why Join Us?

You’ll be joining at the frontier of AI-guided drug discovery, working side-by-side with deep learning experts to build a platform capable of efficiently searching through 10^60 chemical possibilities. Your expertise will directly shape the quality and novelty of our candidate compounds, accelerating the path from target to therapy.

About the Role

Pattern is building a next-generation AI-driven drug discovery platform that integrates state-of-the-art structural modeling, generative design, and reinforcement learning agents to explore the vast chemical space for novel small-molecule therapeutics.

We are seeking a Ligand Design & Pose Prediction Lead to guide de novo small-molecule exploration, interpret protein–ligand binding predictions, and prioritize compounds for synthesis/testing. You will work in close partnership with a deep learning specialist to combine cutting-edge AI tools with your medicinal chemistry and structure-based design expertise.

This is a strategic, non-lab role — your primary focus will be to bridge AI outputs with biological and chemical insight, ensuring the most promising designs move forward.

Key Responsibilities

Lead ligand pose prediction workflows using state-of-the-art AI and computational docking tools (e.g., DiffDock, EquiBind, Glide, GOLD).

Evaluate protein–ligand binding interactions for fit, contact quality, and structural plausibility.

Collaborate with AI/deep learning engineers to refine de novo molecular generation strategies using models such as REINVENT, Pocket2Mol, and diffusion-based 3D generators.

Apply drug-likeness, ADMET, novelty, and selectivity criteria to prioritize compound candidates.

Integrate binding mode insights with biological context from Pattern’s Agentix Knowledge Graph to align compounds with target mechanism-of-action.

Generate clear, actionable compound selection lists for partner synthesis and in-vitro testing.

Contribute to feedback loops by incorporating experimental assay data into ongoing model optimization.

Present binding hypotheses, SAR rationale, and prioritization strategies to cross-functional teams.

Qualifications Required

PhD or Masters in Medicinal Chemistry, Chemical Biology, Computational Chemistry, or related discipline (or MSc + 3+ years of relevant experience).

Proven experience in structure-based drug design and ligand pose evaluation.

Strong working knowledge of protein–ligand binding principles (H-bonds, hydrophobic contacts, electrostatics, shape complementarity).

Familiarity with AI/ML-based molecular design platforms.

Ability to work with predicted protein structures (AlphaFold/OpenFold) and assess binding pockets.

Experience applying drug-likeness rules and property-based filtering in lead prioritization.

Excellent communication skills and ability to work cross-functionally with AI engineers, biologists, and medicinal chemists.

Preferred

Familiarity with pharmacophore modeling and pocket geometry analysis.

Experience in multi-objective optimization (binding, ADMET, novelty).

Exposure to reinforcement learning-driven compound optimization workflows.

Why Join Us?

You’ll be joining at the frontier of AI-guided drug discovery, working side-by-side with deep learning experts to build a platform capable of efficiently searching through 10^60 chemical possibilities. Your expertise will directly shape the quality and novelty of our candidate compounds, accelerating the path from target to therapy.

• Lead and mentor a team of mechanical design engineers, fostering a collaborative and innovative environment.
• Oversee the entire mechanical design lifecycle, from concept development and feasibility studies to detailed design, prototyping, and validation.
• Develop and implement design strategies and roadmaps aligned with business objectives.
• Ensure designs meet performance, reliability, safety, and cost requirements.
• Utilize advanced CAD software (e.g., SolidWorks, CATIA, AutoCAD) for 3D modeling, drafting, and simulation (FEA, CFD).
• Conduct design reviews, analyze test results, and implement design modifications.
• Collaborate with manufacturing engineers to ensure designs are optimized for production and assembly.
• Manage project timelines, budgets, and resources effectively.
• Stay abreast of emerging technologies and industry best practices in mechanical engineering.
• Prepare comprehensive technical documentation, reports, and specifications.
• Troubleshoot complex mechanical issues and provide effective solutions.
• Contribute to the strategic direction of the engineering department.

• Lead the design and development of complex electrical systems and components for various applications.
• Supervise and mentor a team of electrical engineers, providing technical guidance and performance feedback.
• Develop detailed electrical schematics, wiring diagrams, and control system designs using CAD software (e.g., AutoCAD Electrical, EPLAN).
• Conduct thorough electrical load calculations, power distribution analysis, and safety assessments.
• Perform simulation and analysis of electrical circuits and systems to ensure optimal performance and reliability.
• Collaborate with cross-functional teams, including mechanical engineers, software developers, and project managers, to achieve project goals.
• Manage project timelines, budgets, and resources effectively.
• Ensure compliance with relevant industry standards, codes, and regulations (e.g., IEC, NEC, IS).
• Troubleshoot and resolve electrical design issues during the manufacturing, testing, and commissioning phases.
• Stay abreast of emerging technologies and industry best practices in electrical engineering.
• Contribute to the development of engineering standards and best practices within the team.

• Bachelor's or Master's degree in Electrical Engineering or a related field.
• Minimum of 8 years of progressive experience in electrical design engineering.
• Proven experience in leading engineering teams and managing complex projects.
• Expertise in electrical system design, power electronics, control systems, and instrumentation.
• Proficiency in electrical CAD software and simulation tools.
• Strong understanding of electrical codes, standards, and safety regulations.
• Excellent problem-solving, analytical, and decision-making skills.
• Strong leadership, communication, and interpersonal abilities.
• Experience with PLCs, SCADA systems, and industrial automation is a plus.
• Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities.

• Lead the design and development of complex mechanical systems, sub-systems, and components.
• Utilize advanced CAD software (e.g., SolidWorks, CATIA, AutoCAD) for 3D modeling, drafting, and simulation.
• Perform stress analysis, thermal analysis, and other simulations to validate designs.
• Develop and maintain detailed design documentation, including drawings, specifications, and Bills of Materials (BOMs).
• Collaborate with manufacturing, electrical engineering, and software teams to ensure design integration and manufacturability.
• Conduct design reviews, provide constructive feedback, and ensure compliance with industry standards and project requirements.
• Mentor and guide junior mechanical engineers, fostering their technical development.
• Troubleshoot design issues and implement effective solutions during prototyping and testing phases.
• Research and recommend new materials, technologies, and design methodologies.
• Manage project timelines and deliverables for mechanical design aspects.
• Ensure designs meet performance, cost, and reliability targets.
• Contribute to the continuous improvement of design processes and tools.

• Bachelor's or Master's degree in Mechanical Engineering or a related discipline.
• Minimum of 8 years of progressive experience in mechanical design and product development.
• Extensive experience with 3D CAD modeling and simulation software.
• Strong understanding of materials science, thermodynamics, fluid mechanics, and solid mechanics.
• Proven experience in leading design projects and mentoring engineering teams.
• Excellent analytical, problem-solving, and decision-making skills.
• Strong communication and interpersonal skills, with the ability to effectively collaborate with diverse teams.
• Knowledge of manufacturing processes (e.g., machining, injection molding, stamping).
• Familiarity with FMEA (Failure Mode and Effects Analysis) and other quality tools.
• Experience in product lifecycle management (PLM) systems is a plus.

• Lead the design and planning of civil engineering projects.
• Oversee the development of detailed engineering drawings and specifications.
• Conduct feasibility studies and site analyses.
• Ensure compliance with building codes, regulations, and safety standards.
• Manage project budgets, timelines, and resources effectively.
• Provide technical guidance and mentorship to engineering teams.
• Collaborate with architects, contractors, and other stakeholders.
• Perform complex engineering calculations and structural analyses.
• Review and approve design modifications and construction submittals.
• Contribute to business development and client relationship management.

• Bachelor's or Master's degree in Civil Engineering.
• Minimum 10 years of experience in civil engineering design.
• Proven experience in a lead or senior engineering role.
• Proficiency in CAD software (e.g., AutoCAD Civil 3D, Revit).
• Strong knowledge of structural design, geotechnical, or transportation engineering.
• Professional Engineer (PE) license is highly desirable.
• Excellent leadership, communication, and project management skills.
• Strong analytical and problem-solving abilities.
• Experience in managing multiple complex projects simultaneously.
• Ability to foster innovation and teamwork.