BRN Discussion Ongoing

[manny100]

Great find, @Bennysmadness!

I checked out Devansh Lingamaneni’s LinkedIn profile and noticed he had reposted the following post about his Infosys ARC (Applied Research Centre) team having recently presented a live neuromorphic computing demo at Celebrating Tech 2025 (Infosys Bangalore DC’s flagship technology event in November), which in turn led me to a couple of other Infosys employees’ LinkedIn profiles.

Among them that of Senior Consultant Manish Kolachalam, who states that their research with regard to neuromorphic computing does not only relate to drones but also to “improved methods for Traffic Signal Control”:

“- Currently pursuing solutions in applications of Neuromorphic Computing and Swarm Intelligence to Autonomous Machines
- Projects include Object Detection using Spiking Neural Networks in event data, heuristics for drone task allocation and improved methods for Traffic Signal Control”

#infosys #icets #topazfabric #appliedresearch #livinglabs #neuromorphiccomputing #innovation #techfestival | Sandeepan Deka

Day 1 at Celebrating tech BLGR DC - Unlocking Grande Finale was a blast. At the iCETS booth, we showcased Topaz Fabric, our Applied Research Centre, Living Labs, and the wider innovation ecosystem. We kept the crowd buzzing with quick quizzes about our sub units and their offerings- and people...

www.linkedin.com

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https://www.linkedin.com/in/manish-kolachalam-99908147/

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#infosys #icets #infosystopazfabric #appliedresearch #livinglabs #neuromorphiccomputing #innovation #techfestival #bangaloredc #icetsmarketing | Himanshu Thakre

The past two days at 'Celebrating Tech @ Bangalore DC' have been insightful and rewarding for the iCETS team. Our booth welcomed steady engagement as visitors explored Infosys Topaz Fabric, our Applied Research Centre initiatives, Living Labs, and the broader innovation ecosystem. We also had...

www.linkedin.com

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Himanshu Thakre - Infosys | LinkedIn

I’ve always believed marketing is less about chasing metrics and more about crafting… · Experience: Infosys · Education: INDUS BUSINESS ACADEMY - IBA, BANGALORE · Location: Bengaluru · 500+ connections on LinkedIn. View Himanshu Thakre’s profile on LinkedIn, a professional community of 1 billion...

www.linkedin.com

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Wow, great research Frangipani.
Hope you do not mind but i copied it over on the crapper. They need a lift over there. Said it was from you.

 

[manny100]

IMO BrainChip does have the beginnings of a moat in the neuromorphic edge‑AI market — not a full on moat yet, but a real, advantage built on technology, patents, and timing.
The deeper you dig the more obvious it is that’s genuinely hard for others to copy.
1. Patents = The IP wall is real
2. Low power.
3. On chip learning which is a great advantage for Drones, Robotics, Cybersecurity, IOT.
Most competitors cannot come close.
4. Full ecosystem including all the tools, eg Akida Cloud (no hardware needed to test), Akida Development Hub, Model Zoo.
5. Partnerships some starting to bear fruit now, eg, Onsor, Frontgrade, Bascom Hunter, RTX/US/AFRL and Parsons.
No doubt we still have a long way to go but we are getting there.

 

[Frangipani]

It was just a question of time…

“Intel Labs is seeking a distinguished researcher to advance state-of-the-art neuromorphic processor technology to commercial deployment.”

Principal Engineer, Neuromorphic Processor Research

Job Details: Job Description: For nearly a decade, Intel's Neuromorphic Computing Lab-together with a global ecosystem of 250+ research groups-has explored architectures, algorithms, and software inspired by the brain's extraordinary efficiency, scalability, and adaptability. Our Loihi series of...

intel.wd1.myworkdayjobs.com

Principal Engineer, Neuromorphic Processor Research​

Apply

locations Virtual US

time type Full time

posted on Posted Yesterday

time left to apply End Date: January 23, 2026 (30+ days left to apply)

job requisition idJR0279310

​

Job Details:​

Job Description:​

For nearly a decade, Intel's Neuromorphic Computing Lab-together with a global ecosystem of 250+ research groups-has explored architectures, algorithms, and software inspired by the brain's extraordinary efficiency, scalability, and adaptability. Our Loihi series of research chips pioneered event-driven, sparse, and massively parallel neuro-inspired processing, fueling over 100 peer-reviewed publications that validate the promise of this novel approach.

Now, we're entering an exciting new chapter: transforming these breakthroughs into real-world products that will power the coming era of physical AI systems-beyond the reach of GPUs and mainstream AI accelerators.

If you're passionate about pushing the boundaries of computing, from transistor-level innovation to software abstractions, join us. Help define the next wave of AI technology that unites the proven strengths of neuromorphic computing with the versatility demanded by modern AI workloads.

Intel Labs is seeking a distinguished researcher to advance state-of-the-art neuromorphic processor technology to commercial deployment. Responsibilities will include modeling, prototyping, and defining architecture and algorithms that enable orders of magnitude gains for real-world customer applications. The role requires strategic collaboration with a broad range of architects, PIs, and researchers leads spanning Intel, industry, government and academic groups.

Qualifications:​

Minimum qualifications:
• PhD in Computational Neuroscience, Computer Science, Electrical/Computer Engineering, or a related field. • 20+ years of combined industry and academic experience. • 5+ years of experience in computer science, architecture, or algorithms research with 10+ peer-reviewed publications. • 5+ years of software development for high-performance numerical/parallel/AI applications • 3+ years of experience developing for specialized architectures, e.g. neuromorphic, FPGA, HPC.

Preferred qualifications:
• Publications in the fields of AI/ML algorithms and architecture • Product development experience from technology research to customer deployment • 3+ years of hardware architecture and design experience • 3+ years of management experience

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Job Type:​

Experienced Hire

Shift:​

Shift 1 (United States of America)

Primary Location:​

Virtual US

Additional Locations:​

Business group:​

As a member of the Chief Technology Office, Artificial Intelligence, and Network and Edge Group (CTO AI NEX), you will be committed to strategically penetrating the AI market by delivering disruptive and transformative solutions. Your focus will be on leveraging technology innovation and incubation to drive commercial success, ensuring that advancements create significant value. The team is dedicated to driving the software-defined transformation of the world's networks profitably, setting new standards for efficiency and connectivity. Through these priorities, you aim to lead the way in technological evolution and redefine the future of global networks.

Posting Statement:​

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

​

Position of Trust​

This role is a Position of Trust. Should you accept this position, you must consent to and pass an extended Background Investigation, which includes (subject to country law), extended education, SEC sanctions, and additional criminal and civil checks. For internals, this investigation may or may not be completed prior to starting the position. For additional questions, please contact your Recruiter.


Benefits:

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here:
https://intel.wd1.myworkdayjobs.com/External/page/1025c144664a100150b4b1665c750003


Annual Salary Range for jobs which could be performed in the US: $214,730.00-303,140.00 USD


The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.



Work Model for this Role

This role is available as a fully home-based and generally would require you to attend Intel sites only occasionally based on business need. However, you must live and work from the country specified in the job posting, in which Intel has a legal presence. Due to legal regulations, remote work from any other country is unfortunately not permitted. * Job posting details (such as work model, location or time type) are subject to change.The application window for this job posting is expected to end by 01/23/2026

 

[7für7]

New job

#hiring | BrainChip

We're #hiring a new Digital Design Engineer (MPU) in Laguna Hills, California. Apply today or share this post with your network.

www.linkedin.com

 

[manny100]

Based on our known partnerships, ecosystem, Oncor, Parsons, Frontgrade Gaisler, RTX/USAFRL, Bascom-Hunter, Steve Brightfields recent comments and expected GEN ai and GEN 3 I asked chat to put together a table showing briefly what it all signals to investors.
Its common sense but puts it all together in the one spot.

What BrainChip’s Partnerships & Roadmap Signal to Investors​

Category	Message to Investors
Onsor partnership	Validates Akida in medical‑grade, real‑time, ultra‑low‑power applications (seizure‑detecting glasses). Shows the tech works where latency and power matter most.
Frontgrade Gaisler integration	Confirms Akida is suitable for radiation‑hardened, space‑grade SoCs. Space customers only adopt tech that is extremely reliable and efficient.
Parsons / Blue Ridge Envisioneering	Demonstrates traction in defense edge‑AI systems, where ruggedness, low power, and real‑time inference are mandatory.
Bascom Hunter / Navy SBIR	Shows adoption in DoD‑aligned programs and rugged neuromorphic hardware (SNAP card). Their purchase of Akida‑1500 chips signals real demand.
RTX / USAFRL expansion	A major aerospace/defense contractor expanding trials after “surprising results” is a strong technical endorsement. Suggests Akida outperformed expectations.
Akida‑1500 tape‑out	Indicates BrainChip is executing, not just promising. Tape‑out means the design is real, stable, and ready for manufacturing.
GenAI roadmap	Shows BrainChip is aligning with the biggest trend in tech: on‑device generative AI. Signals long‑term relevance.
Gen3 architecture direction	Confirms BrainChip is not a one‑chip company. A maturing roadmap increases investor confidence in future revenue streams.
Multiple partnerships across sectors	Demonstrates broad applicability: medical, defense, aerospace, industrial, space, consumer. Reduces single‑market risk.
Customers requesting chips before licensing	Strongest sign of commercial readiness. Customers want hardware validation before committing to IP licensing — a normal path toward high‑margin revenue.
Hearing‑aid adoption accelerating	Hearing aids are a high‑volume consumer vertical. Early adoption signals potential for recurring, scalable revenue.

 

[manny100]

At the 25 minute mark of Steve Brightfields interview he said Ear buds will become medically certified hearing aids off the shelf. That is potentially huge.
Disaster for hearing aid producers and sellers?
At 28 min on he says we have a customer with smart glasses and they can detect from brainwave activity whether it be migraine, in this case detecting Epileptic seizures before it happens.
That looks a giveaway that Migraine prediction is being worked on at least - another Onsor project?
Migraine detecton would be huge.

 

[7für7]

At the 25 minute mark of Steve Brightfields interview he said Ear buds will become medically certified hearing aids off the shelf. That is potentially huge.
Disaster for hearing aid producers and sellers?
At 28 min on he says we have a customer with smart glasses and they can detect from brainwave activity whether it be migraine, in this case detecting Epileptic seizures before it happens.
That looks a giveaway that Migraine prediction is being worked on at least - another Onsor project?
Migraine detecton would be huge.

Interesting… but what could someone do against migraine? Take the pill earlier?

 

[manny100]

It's interesting that Arquimea and Brainchip made an agreement concerning water safety and rescue.
" ARQUIMEA has demonstrated BrainChip’s Akida with a Prophesee event-based Metavision® camera on a low-power drone to detect distressed swimmers and surfers, helping lifeguards scale their services for large beach areas."
Edge AI Empowers Search & Rescue Operations
The date of the Brainchip news release was 16th April 2025.
By coincidence Arquimea on 22nd April 2025 announced that on "14th April 2025 that they and Lockheed Martin Skunk Works have successfully completed development of an enhanced anomaly detection for Intelligence, Surveillance and Reconnaissance (ISR) platforms such as Drones and other systems piloted by artificial intelligence agents....."
"neural networks", " using machine learning algorithms, allowing the mission to be readapted".
Neural networks, adaptive on chip learning? Sounds like something AKIDA can do.
Arquimea and Lockheed Martin develop advanced AI surveillance and reconnaissance (ISR) systems
I note that Brainchip has ties with both Lockheed Martin and Arquimea.
I also note that both Lockheed Martin and Arquimea are defense suppliers.

 

[Fullmoonfever]

Seems Honeywell through their owned CAES entity are another defence player looking to develop neuromorphic/ cognitive and would like someone preferably with experience with the likes of Akida / Loihi hardware. My bold.

CAES hiring Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW) in San Jose, CA | LinkedIn

Posted 9:42:45 AM. Delivering mission-critical, electronic solutions that protect lives. Use your creativity and…See this and similar jobs on LinkedIn.

www.linkedin.com

Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW)​

CAES San Jose, CA
1 week ago Be among the first 25 applicants​

Delivering mission-critical, electronic solutions that protect lives. Use your creativity and critical thinking to take our products from concept to customer.

At CAES by Honeywell, we engineer solutions for the world’s most critical missions. We serve customers in the defense and aerospace markets. Seeking a career that offers challenging, diverse projects and opportunities? Looking for a position with a company that offers long-term professional advancement? Searching for a place that values a diverse, team-based environment? One that values YOU. Consider CAES by Honeywell.

The most important thing we build is TRUST

#CustomerFocus #Values #Leader #TogetherWePioneer

Overview

We’re seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer to architect, design, and develop advanced AI/ML systems that power our next generation of products. In this leadership role, you’ll contribute to the technical roadmap, mentor engineering teams, and collaborate with cross-functional teams to deliver intelligent, scalable, and production-ready AI and machine learning technologies. You will be responsible for researching, creating, adapting and evaluating AI/ML techniques to solve complex customer problems with real-time solutions to support our defense customers.

Specifically, we are building next-generation cognitive electronic warfare systems that operate autonomously at the tactical edge in contested, low-SWaP (Size, Weight, and Power), denied, and disconnected environments. This is not a prompt-engineering or GenAI role. We are looking for hardcore AI/ML systems engineers who treat machine learning as a component of a larger, mission-critical, real-time embedded system.

Responsibilities

Major Duties & Responsibilities:

• Design, implement, and harden on-line and continual-learning ML algorithms for RF signal classification, adaptive jamming, cognitive radar, and electronic attack/support decision engines.
• Port, optimize, and deploy ML inference algorithms to edge processors.
• Build and maintain low-latency, deterministic inference pipelines that integrate tightly with real-time RF front-ends and digital signal processing chains.
• Lead the systems integration of AI/ML techniques into mission-critical embedded platforms running real-time operating systems.
• Design and deliver warfighter-focused engineering visualizations and tactical displays (real-time spectrum awareness, threat emitter tracks, cognitive EW decision overlays, confidence heatmaps) using modern web stack frameworks that run natively on embedded tactical processors and dismounted soldier systems.
• Own the MLOps and DevSecOps pipeline for classified EW programs: secure CI/CD, model versioning, containerized build/test/deploy, SBOM generation, and compliance with DoD zero-trust and CNCF security standards.
• Architect and deploy Kubernetes-based edge orchestration clusters (e.g. k3s) that operate in fully air-gapped tactical environments with strict latency and availability requirements.
• Perform end-to-end performance profiling (memory bandwidth, cache coherency, DMA, GPU/TPU/NPU utilization).
• Review code, guide architecture decisions, and mentor the AI/ML engineering team.
• Collaborate with product and engineering teams to identify AI/ML-driven opportunities.
  

Qualifications

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field
• 7+ years of professional experience shipping production AI/ML systems, ideally in defense, aerospace, or autonomous systems
• Prior work on DoD cognitive EW programs
• Deep expertise in high-performance and real-time applications (not just scripting wrappers)
• Real-time and embedded application programming (no Python-only backgrounds)
• Proven track record of deploying AI/ML solutions to cloud and edge/constrained devices
• Strong systems engineering background: you understand clocks, interrupts, DMA, cache hierarchies, memory-mapped I/O, and real-time scheduling
• Hands-on experience building and securing CI/CD pipelines for classified or regulated environments
• Expertise with Docker, container hardening, and Kubernetes in disconnected/edge configurations (k3s, microk8s, Rancher Harvester).
• Familiarity with RF/ML intersections: signal detection & classification, modulation recognition, emitter geolocation, fingerprinting, adaptive waveform design, or reinforcement learning for EW
• Proficiency with ML algorithms (including NLP, Computer Vision, time-series), libraries including foundational understanding and expertise in statistics probability theory and linear algebra
• Strong understanding of machine learning fundamentals: supervised/unsupervised learning, deep learning, model evaluation, optimization, feature engineering, etc
• Experience with data engineering workflows and building robust training datasets
  

Preferred Qualifications

• Experience as the technical lead for establishing and accrediting classified AI/ML information systems under the DoD Risk Management Framework (RMF):
  • Author and maintain System Security Plans (SSP), Security CONOPS, and AI/ML-specific risk annexes
  • Build and harden multi-enclave classified development, integration, and operational environments (RHEL 8/9, SELinux enforcing, DISA STIGs, Assured Compliance Assessment Solution (ACAS))
  • Lead the creation of AI/ML-specific artifacts for eMASS packages, including model cards, data provenance, adversarial robustness testing, and continuous monitoring plans
  • Obtain and maintain Authority to Operate (ATO) for classified cognitive EW systems containing advanced GPU/NPU-accelerated AI infrastructure
• Perform Linux systems administration at the classified level: kernel tuning for real-time determinism, custom security hardening, cross-domain solution integration, auditd/ELK stack management, and FIPS 140-3 compliant cryptography
• Deep Linux systems administration and hardening experience in classified environments (RHEL/CentOS, STIG compliance, SELinux policy authoring).
• Hands-on experience authoring RMF packages and obtaining ATOs for systems containing machine learning components for the U.S. Government (Army, Navy, Air Force, or IC customer)
• Expertise with Docker, container hardening (CIS, OSCAP), and Kubernetes in disconnected tactical environments
• Experience or exposure with implementing Government reference architectures
• Experience with neuromorphic or spiking neural network hardware (Intel Loihi, BrainChip Akida)
• Experience with distributed training, GPU acceleration, and high-performance ML compute
• Strong background in foundation algorithms, transformers, or multimodal AI
• Knowledge of automated model monitoring, drift detection, and lifecycle management
• Experience integrating ML models into consumer or enterprise products

 

[Bravo]

 

[Diogenese]

Seems Honeywell through their owned CAES entity are another defence player looking to develop neuromorphic/ cognitive and would like someone preferably with experience with the likes of Akida / Loihi hardware. My bold.

CAES hiring Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW) in San Jose, CA | LinkedIn

Posted 9:42:45 AM. Delivering mission-critical, electronic solutions that protect lives. Use your creativity and…See this and similar jobs on LinkedIn.

www.linkedin.com

Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW)​

CAES San Jose, CA​

1 week ago Be among the first 25 applicants​

Delivering mission-critical, electronic solutions that protect lives. Use your creativity and critical thinking to take our products from concept to customer.

At CAES by Honeywell, we engineer solutions for the world’s most critical missions. We serve customers in the defense and aerospace markets. Seeking a career that offers challenging, diverse projects and opportunities? Looking for a position with a company that offers long-term professional advancement? Searching for a place that values a diverse, team-based environment? One that values YOU. Consider CAES by Honeywell.

The most important thing we build is TRUST

#CustomerFocus #Values #Leader #TogetherWePioneer

Overview

We’re seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer to architect, design, and develop advanced AI/ML systems that power our next generation of products. In this leadership role, you’ll contribute to the technical roadmap, mentor engineering teams, and collaborate with cross-functional teams to deliver intelligent, scalable, and production-ready AI and machine learning technologies. You will be responsible for researching, creating, adapting and evaluating AI/ML techniques to solve complex customer problems with real-time solutions to support our defense customers.

Specifically, we are building next-generation cognitive electronic warfare systems that operate autonomously at the tactical edge in contested, low-SWaP (Size, Weight, and Power), denied, and disconnected environments. This is not a prompt-engineering or GenAI role. We are looking for hardcore AI/ML systems engineers who treat machine learning as a component of a larger, mission-critical, real-time embedded system.

Responsibilities

Major Duties & Responsibilities:

• Design, implement, and harden on-line and continual-learning ML algorithms for RF signal classification, adaptive jamming, cognitive radar, and electronic attack/support decision engines.
• Port, optimize, and deploy ML inference algorithms to edge processors.
• Build and maintain low-latency, deterministic inference pipelines that integrate tightly with real-time RF front-ends and digital signal processing chains.
• Lead the systems integration of AI/ML techniques into mission-critical embedded platforms running real-time operating systems.
• Design and deliver warfighter-focused engineering visualizations and tactical displays (real-time spectrum awareness, threat emitter tracks, cognitive EW decision overlays, confidence heatmaps) using modern web stack frameworks that run natively on embedded tactical processors and dismounted soldier systems.
• Own the MLOps and DevSecOps pipeline for classified EW programs: secure CI/CD, model versioning, containerized build/test/deploy, SBOM generation, and compliance with DoD zero-trust and CNCF security standards.
• Architect and deploy Kubernetes-based edge orchestration clusters (e.g. k3s) that operate in fully air-gapped tactical environments with strict latency and availability requirements.
• Perform end-to-end performance profiling (memory bandwidth, cache coherency, DMA, GPU/TPU/NPU utilization).
• Review code, guide architecture decisions, and mentor the AI/ML engineering team.
• Collaborate with product and engineering teams to identify AI/ML-driven opportunities.

Qualifications

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field
• 7+ years of professional experience shipping production AI/ML systems, ideally in defense, aerospace, or autonomous systems
• Prior work on DoD cognitive EW programs
• Deep expertise in high-performance and real-time applications (not just scripting wrappers)
• Real-time and embedded application programming (no Python-only backgrounds)
• Proven track record of deploying AI/ML solutions to cloud and edge/constrained devices
• Strong systems engineering background: you understand clocks, interrupts, DMA, cache hierarchies, memory-mapped I/O, and real-time scheduling
• Hands-on experience building and securing CI/CD pipelines for classified or regulated environments
• Expertise with Docker, container hardening, and Kubernetes in disconnected/edge configurations (k3s, microk8s, Rancher Harvester).
• Familiarity with RF/ML intersections: signal detection & classification, modulation recognition, emitter geolocation, fingerprinting, adaptive waveform design, or reinforcement learning for EW
• Proficiency with ML algorithms (including NLP, Computer Vision, time-series), libraries including foundational understanding and expertise in statistics probability theory and linear algebra
• Strong understanding of machine learning fundamentals: supervised/unsupervised learning, deep learning, model evaluation, optimization, feature engineering, etc
• Experience with data engineering workflows and building robust training datasets

Preferred Qualifications

• Experience as the technical lead for establishing and accrediting classified AI/ML information systems under the DoD Risk Management Framework (RMF):
  • Author and maintain System Security Plans (SSP), Security CONOPS, and AI/ML-specific risk annexes
  • Build and harden multi-enclave classified development, integration, and operational environments (RHEL 8/9, SELinux enforcing, DISA STIGs, Assured Compliance Assessment Solution (ACAS))
  • Lead the creation of AI/ML-specific artifacts for eMASS packages, including model cards, data provenance, adversarial robustness testing, and continuous monitoring plans
  • Obtain and maintain Authority to Operate (ATO) for classified cognitive EW systems containing advanced GPU/NPU-accelerated AI infrastructure
• Perform Linux systems administration at the classified level: kernel tuning for real-time determinism, custom security hardening, cross-domain solution integration, auditd/ELK stack management, and FIPS 140-3 compliant cryptography
• Deep Linux systems administration and hardening experience in classified environments (RHEL/CentOS, STIG compliance, SELinux policy authoring).
• Hands-on experience authoring RMF packages and obtaining ATOs for systems containing machine learning components for the U.S. Government (Army, Navy, Air Force, or IC customer)
• Expertise with Docker, container hardening (CIS, OSCAP), and Kubernetes in disconnected tactical environments
• Experience or exposure with implementing Government reference architectures
• Experience with neuromorphic or spiking neural network hardware (Intel Loihi, BrainChip Akida)
• Experience with distributed training, GPU acceleration, and high-performance ML compute
• Strong background in foundation algorithms, transformers, or multimodal AI
• Knowledge of automated model monitoring, drift detection, and lifecycle management
• Experience integrating ML models into consumer or enterprise products

Hi Fmf,

That's some hardrcore qualifications they are calling for.

This is not your summer intern.