PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE Apply now
PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE

PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE

London Full-Time 72000 - 108000 £ / year (est.)
Apply now
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At a Glance

  • Tasks: Lead the development of a cutting-edge ML platform for aerospace and defense.
  • Company: Join Bullisher, a fintech innovator transforming a $3 trillion industry.
  • Benefits: Enjoy a dynamic work environment with opportunities for professional growth.
  • Why this job: Be at the forefront of AI/ML technology, impacting real-time decision-making.
  • Qualifications: 20+ years in software development, expertise in ML tools like PyTorch and TensorFlow.
  • Other info: Must be authorized to work in the UK; no visa sponsorship available.

The predicted salary is between 72000 - 108000 £ per year.

PRINCIPAL MACHINE LEARNING INFRASTRUCTURE (ML PLATFORM AND OPERATIONS) – ENGINEERS:

Bullisher is a data-centric fintech solution provider in the aerospace and defense industry for institutional-level investors, looking to disrupt and revolutionize a $3 trillion industry. We spearhead an industry-leading Blackbox to facilitate and administer trade agreements, delivering solutions through innovation with uncompromising agility.

JOB DESCRIPTION:

As a newly created role for a team of four, the oversight team requires a PLATFORM DESIGNED TO HANDLE COMPLEX WORKLOADS. This involves a machine learning development system, a specialized infrastructure needed to deliver complex AI/ML workloads focused on training deep learning models to improve distributed training and hyperparameter optimization techniques across GPU clusters without rewriting code or restructuring infrastructure.

Areas to focus on will include a custom-built internal ML software infrastructure, enabling AI and workloads to run on the same infrastructure. This is a software-only development project for MULTIPLE CROSS DOMAIN PLATFORMS. The role focuses on a solution-level-based ML development training, including hardware, software, validated and pre-configured solutions. The work will be performed out of the electromagnetic spectrum and radio spectrum, impacting real-time decision-making and execution.

WHAT ARE WE LOOKING FOR:

  • Extensive experience in ML development in PYTORCH , Kubernetes, and TensorFlow.
  • A proven record in AI and machine learning, focusing on end-to-end solution integration with existing infrastructure.
  • A leading developer focused on transparent model reporting with the utilization of AI infrastructure and ML team collaboration.
  • Academic leadership in transformative ML-powered application workflows.
  • Experience deploying ML models to production environments.
  • Experience with MLOps infrastructure for robust deployment and performance.
  • Experience in high-performance integrated systems management for metrics, benchmark performance, and real-time alerts management.
  • Hands-on big data analytics, advanced analytics, and machine learning development system roadmap.
  • Highly skilled in data acquisition and preparation.
  • Proficient with model deployment and inference.
  • Executive-level experience in model development and training.

PHYSICAL DEMANDS: This position requires the ability to communicate and exchange information, utilize equipment necessary to perform the job, and move about the office.

ENVIRONMENT: This position will operate in the regulatory engineering division, MULTIDOMAIN DEFENCE DOCK.

Employees must be legally authorized to work in the UK. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is not available for this position.

KEY REQUIREMENTS:

  • Professional in ML operationalization, including workflow/model management, machine learning development environment (MLDE) management Node, MLOps flow.
  • 20+ years of experience in professional software development.
  • Strong programming skills.
  • Great skills in data engineering and big data technologies.
  • Highly skilled with object-orientation and software development best practices.
  • Offensive Security Certified Professional (OSCP) .
  • Certified Information Security Manager (CISM) .
  • Information Systems Security Architecture Professional (ISSAP) is essential.
  • Certified Authorization Professional (CAP) .
  • Information Assurance System Architecture and Engineer (IASAE) .
  • It is prerequisite to be certified in one of the listed DoD 8570 Certifications.

INTERVIEW PROCESS:

  • STAGE 1: COGNITIVE ABILITY TEST
  • STAGE 2: COGNITIVE ASSESSMENT SCREENING: WITH A 30+ YEARS EXPERIENCE PSYCHOLOGIST
  • STAGE 3: PRE-SCREENING (verification checks & DV security clearance)
  • STAGE 4: INTERVIEW WITH THE CEO, CTO & GC

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PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE employer: Gentrian

At Bullisher, we pride ourselves on being an exceptional employer in the aerospace and defense sector, offering a dynamic work environment that fosters innovation and collaboration. Our commitment to employee growth is evident through our focus on cutting-edge machine learning technologies and the opportunity to work alongside industry leaders in a supportive culture that values transparency and excellence. Located in the heart of the UK, our team enjoys not only competitive benefits but also the chance to make a significant impact in a transformative industry.
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Contact Detail:

Gentrian Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE

✨Tip Number 1

Familiarize yourself with the specific technologies mentioned in the job description, such as PyTorch, Kubernetes, and TensorFlow. Having hands-on experience or projects that showcase your skills in these areas will make you stand out during the interview process.

✨Tip Number 2

Prepare to discuss your experience with MLOps infrastructure and how you've successfully deployed ML models in production environments. Be ready to provide examples of challenges you've faced and how you overcame them.

✨Tip Number 3

Since this role involves collaboration across multiple domains, think about instances where you've worked in cross-functional teams. Highlight your ability to communicate complex technical concepts to non-technical stakeholders.

✨Tip Number 4

Given the emphasis on security certifications, ensure you can articulate how your certifications (like OSCP, CISM, etc.) have influenced your approach to machine learning infrastructure. This will demonstrate your commitment to best practices in security and compliance.

We think you need these skills to ace PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE

Extensive experience in ML development with PyTorch
Proficiency in Kubernetes and TensorFlow
End-to-end solution integration expertise
Transparent model reporting skills
Academic leadership in ML-powered application workflows
Experience deploying ML models to production environments
MLOps infrastructure knowledge
High-performance integrated systems management
Hands-on big data analytics experience
Advanced analytics capabilities
Data acquisition and preparation skills
Model deployment and inference proficiency
Executive-level experience in model development and training
Strong programming skills
Data engineering and big data technologies expertise
Object-oriented programming knowledge
Software development best practices
Offensive Security Certified Professional (OSCP)
Certified Information Security Manager (CISM)
Information Systems Security Architecture Professional (ISSAP)
Certified Authorization Professional (CAP)
Information Assurance System Architecture and Engineer (IASAE)

Some tips for your application 🫡

Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Principal Machine Learning Infrastructure Engineer position. Familiarize yourself with the technologies mentioned, such as PyTorch, Kubernetes, and TensorFlow.

Tailor Your CV: Customize your CV to highlight your extensive experience in machine learning development and software engineering. Emphasize your skills in MLOps, model deployment, and any relevant certifications like OSCP or CISM.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the aerospace and defense industry. Discuss how your background aligns with the company's mission to disrupt the fintech space and your experience with complex AI/ML workloads.

Prepare for the Interview Process: Since the interview process includes cognitive ability tests and assessments, practice relevant questions and scenarios. Be ready to discuss your past projects and how they relate to the role's requirements.

How to prepare for a job interview at Gentrian

✨Showcase Your Technical Expertise

Be prepared to discuss your extensive experience with ML development in PyTorch, Kubernetes, and TensorFlow. Highlight specific projects where you successfully integrated AI solutions into existing infrastructures.

✨Demonstrate Leadership Skills

Since this role involves leading a small team, share examples of how you've guided teams in the past. Discuss your approach to fostering collaboration and transparency in model reporting.

✨Prepare for Cognitive Assessments

Understand that the interview process includes cognitive ability tests and assessments. Brush up on relevant concepts and practice problem-solving exercises to perform well in these stages.

✨Align with Company Values

Research Bullisher's mission to disrupt the aerospace and defense industry. Be ready to articulate how your skills and experiences align with their goals of innovation and agility in delivering complex ML solutions.

PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE
Gentrian Apply now
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  • PRINCIPAL MACHINE LEARNING INFRASTRUCTURE ENGINEERS-AEROSPACE AND DEFENSE

    London
    Full-Time
    72000 - 108000 £ / year (est.)
    Apply now

    Application deadline: 2027-01-08

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    Gentrian

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