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Ai Chip Design Rtl Jobs in New York (NOW HIRING)

Lantern

Senior Lead, AI Automation

New York, NY · On-site

Ultimately, this role directly impacts Lantern's ability to deliver care to members, win blue-chip ... Design and build AI solutions that resolve the root cause, rather than bolting automation onto a ...

Lantern

Senior Lead, AI Automation

New York, NY

Ultimately, this role directly impacts Lantern's ability to deliver care to members, win blue-chip ... Design and build AI solutions that resolve the root cause, rather than bolting automation onto a ...

Nokia

Photonics Layout and Tooling Engineer

Manhattan, NY · On-site

$105K - $195K/yr

  • Medical

  • Dental

  • Life

  • Retirement

  • PTO

... design and fabrication to testing and analysis, for complex photonic devices and systems-on-chip ... Experience with directing and reviewing agentic AI systems. About Us Advancing connectivity to ...

Nokia

Photonics Layout and Tooling Engineer

Manhattan, NY

  • Medical

  • Dental

  • Life

  • Retirement

  • PTO

Experience with directing and reviewing agentic AI systems. * Design, develop, and maintain applications and scripts to automate tools and workflows within the photonic chip fabrication process.

P2P

Senior FPGA Engineer

Manhattan, NY · On-site

$225 - $325/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Strong skills in RTL logic design (Verilog) and verification; 2+ years of experience writing ... Experience with the design of system-on-chip (SOC) architectures, memory & processor subsystems ...

DRW

Senior FPGA Engineer

New York, NY · On-site

$225K - $325K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Strong skills in RTL logic design (Verilog) and verification; 2+ years of experience writing ... Experience with the design of system-on-chip (SOC) architectures, memory & processor subsystems ...

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All JobsAi Chip Design Rtl JobsAi Chip Design Rtl Jobs in New York

Ai Chip Design Rtl information

What is the difference between Ai Chip Design Rtl vs Ai Chip Verification Engineer?

AspectAi Chip Design RtlAi Chip Verification Engineer
Primary FocusDeveloping and implementing Register Transfer Level (RTL) code for AI chipsVerifying and validating RTL designs to ensure functionality
Skills RequiredHDL languages (Verilog/VHDL), digital design, FPGA/ASIC knowledgeSimulation, testbench creation, debugging, scripting skills
Work EnvironmentDesign teams, hardware development labs, EDA toolsVerification teams, simulation environments, test setups
CertificationsHardware design certifications, FPGA/ASIC trainingVerification methodologies, UVM, SystemVerilog certifications

While Ai Chip Design Rtl focuses on creating the hardware description code for AI chips, Ai Chip Verification Engineer ensures that the RTL design functions correctly through rigorous testing. Both roles require knowledge of HDL languages and work closely within hardware development teams, but their core responsibilities differ—design versus verification.

What are common challenges faced by AI Chip Design RTL engineers during the verification process?

AI Chip Design RTL engineers often encounter challenges in ensuring their designs meet complex functional and performance requirements, especially given the rapid pace of AI hardware advancements. Verification can be particularly demanding due to the need to simulate and test intricate AI workloads, manage large datasets, and debug subtle timing or logic errors. Collaboration with verification teams, system architects, and software engineers is essential to address these issues efficiently and to ensure seamless integration of the RTL code into the broader chip design. Staying up-to-date with the latest verification tools and methodologies is also crucial for success in this role.

What is an AI Chip Design RTL engineer?

AI Chip Design RTL (Register Transfer Level) engineers are specialists who design the digital logic for chips used in artificial intelligence applications. They use hardware description languages like Verilog or VHDL to create and validate the architecture and functionality of these chips before they are manufactured. Their work ensures that AI processors are efficient, high-performing, and meet the requirements of modern AI workloads. RTL engineers collaborate closely with verification, software, and hardware teams to optimize chip performance and power consumption.

What skills and qualifications are needed to thrive as an AI Chip Design RTL engineer?

To thrive as an AI Chip Design RTL Engineer, you need a solid background in digital design, computer architecture, and proficiency in Hardware Description Languages (HDLs) like Verilog or VHDL, often supported by a degree in electrical or computer engineering. Experience with simulation tools (e.g., ModelSim, Synopsys), ASIC/FPGA design flows, and relevant certifications are highly valued. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills help you excel in collaborative and complex design environments. These competencies are crucial for creating efficient, reliable AI hardware that meets performance and power requirements in a fast-evolving field.

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Infographic showing various Ai Chip Design Rtl job openings in New York as of August 2026, with employment types broken down into 87% Full Time, 9% Part Time, and 4% Contract. Highlights an 92% In-person, and 8% Remote job distribution.

Senior Bioinformatics Analyst (AI/ML for Genomics) | Bioinformatics Resource Center

The Rockefeller University

Manhattan, NY • On-site

Full-time

Re-posted 20 days ago

Job description

Job Summary:
The Rockefeller University is a leading research institution, and they are seeking a Senior Bioinformatics Analyst to design, implement, and deploy AI/ML methods for genomics and multi-omics data. This role focuses on creating robust analytical pipelines that support research across the university's laboratories and providing consultative support and training to researchers.
Responsibilities:
• Design, implement, and maintain AI/ML pipelines for genomics and multi-omics data (RNA-seq, ATAC-seq, ChIP-seq, functional genomics)
• Apply and adapt machine learning and deep learning models (e.g., convolutional and transformer-based architectures) to biological questions in collaboration with investigators.
• Develop interpretable models and attribution analyses (e.g., motif discovery, perturbation and variant-effect analyses) to support biological insight.
• Build, document, and containerize reproducible workflows suitable for shared HPC/GPU environments.
• Provide consultative support and training to researchers using BRC AI/ML tools and pipelines.
• Performs related duties & responsibilities as assigned/requested.
Qualifications:
Required:
• Master’s degree in Bioinformatics, Computational Biology, Computer Science, or a related field
• A minimum of five years of relevant experience applying computational or machine learning methods to biological data.
Preferred:
• PhD in Bioinformatics, Computational Biology, Computer Science, or a related field
• Experience applying deep learning or foundation-model approaches to sequence-based or multimodal genomics data.
• Experience in a core facility or highly collaborative research environment.
• Familiarity with model interpretability for biological insight (motif analysis, attribution methods, TF/RBP modeling).
• Experience working with HPC/GPU resources and job schedulers (e.g., Slurm) and/or cloud-based deployments.
• Track record of contributing to peer-reviewed publications as a computational specialist.
• Interest in mentoring and training researchers in applied AI/ML methods.
Company:
The Rockefeller University is a center for research and graduate education in biomedical sciences, chemistry, bioinformatics, and physics. Founded in 1901, the company is headquartered in New York, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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