About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

Open to overseas candidates/Visa Support

This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

In this role, you’ll further improve bidding strategies, audience targeting and creative optimization by deep-diving RTB ecosystem including SSP/DSP/MMP to design the strategy, enhancing user signals or applying advanced deep learning model

What You’ll Work On

• Deep-dive the RTB ecosystem to identify the potential direction and decide the bidding strategy
• Leverage advance deep learning model to improve bidding/audience model performance
• Co-work with teams to improve real-time/long-term user interaction signal collection and to further improve model performance

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of industry experience on RTB ecosystem
• Proficiency in Python and SQL experience with modern ML frameworks and deep learning model (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

#LI-AK1

THE ROLE

The Field Solution Architect (FSA) is the regional business and technical leader for a specific workload, responsible for driving strategy, execution, and measurable business impact and growth for that workload across the assigned geo.  Acting as a Workload Business Owner, the FSA combines deep technical expertise with cross-functional leadership to grow the pipeline, accelerate bookings, and strengthen Everpure’s ecosystem.

The FSA partners closely with district and regional Sales, Sales Engineering, Global Partner Organization, and Marketing leadership to shape and execute go-to-market strategies for their assigned workload. Through annual planning cycles, quarterly sales reviews (QSRs), and ongoing GTM alignment, the FSA advises leadership on market opportunity, customer priorities, and competitive dynamics. By adding workload-specific insights into regional and district strategies, the FSA ensures growth opportunities are clearly represented, prioritized, and translated into actionable plans that drive pipeline creation, bookings, and sustained adoption.

The role requires strong technical depth in Artificial Intelligence, Analytics and/or high performance computing along with a solid understanding of the surrounding ecosystem. Curious and proactive, the FSA drives enablement, knowledge sharing, and new opportunity development to expand Everpure’s impact across the region.

WHAT YOU'LL DO

• Key Responsibilities

  1. Workload Ownership and Business Growth

  Own the business success of your workload across APJ. Operate with a business development mindset and partner with regional GTM leadership to drive structured annual planning, and alignment across sales, SE, marketing and partner organizations.

  Activities:

  • Develop and execute a regional “Workload Business Plan” with measurable goals and actions.
    
    
    
  • Conduct TAM and whitespace analysis to identify growth opportunities.
    
    
    
  • Collaborate with Sales, SE, Marketing, and Partner Leadership to track and execute regional GTM plays for your workload.
    
    
    

   

  • Maintain alignment with HQ and product teams to refine technical messaging (“Why Everpure / Why Now”).
    
    
    
  • Track progress and report quarterly insights and outcomes to leadership.
    
    
    

  2. Strategic Account Engagement

  Take ownership for integrating your solution strategy into the top strategic account Technical Account Plans, ensuring clear actions that drive expansion and sustained workload growth.The FSA acts as a trusted advisor and workload strategist, partnering with account teams, alliance partners, to uncover insights that shape Everpure’s positioning and accelerate workload adoption, pipeline generation, bookings growth.

  • Investigate workload presence within the top-strategic accounts. Understand what the customer is currently using, which vendors and technologies are involved, and where Everpure can add differentiated value.
  • Lead or co-lead strategic pipeline creation customer meetings, workshops, architecture reviews, and workload deep dive sessions
    
    
    
  • Collaborate with alliance and ecosystem partners to gather technical and commercial intelligence that informs competitive strategy and solution fit.
    
    
    
  • Co-develop account-specific workload strategies with AE/SE teams, aligning Everpure’s strengths with the customer’s business priorities.
    
    
    
  • Drive workload-specific opportunity identification, cross-sell, and upsell within key accounts.
    
    
    
  • Lead or support executive briefings (EBCs), roadmap discussions, and innovation workshops to influence long-term architecture decisions.
    
    
    

  3.  Domain Mastery of the Solution

  Be the regional Subject Matter Expert (SME) for the assigned workload demonstrating mastery of both the technology and the sales motion. Align workload strategies and architectures with Everpure Storage’s unique strengths to drive differentiation, technical wins, and measurable customer outcomes.

  • Demonstrate 501-level technical expertise and maintain up-to-date knowledge of the solution area.
    
    
    
  • Proactively drive technical wins in key opportunities and complex deals.
    
    
    
  • Lead architecture reviews, workshops, and technical demonstrations.
    
    
    
  • Provide competitive intelligence, product insights, and updates to the field.
    
    
    
  • Align workload positioning and architectures with Everpure’s platform strengths: Evergreen, simplicity, efficiency, and Enterprise Data Cloud (EDC).
    
    
    
  • Mentor SEs to independently position, design, and size solutions confidently.
    
    
    
  • Maintain readiness of demo environments and FSA lab assets.
    
    
    
    

  4. Ecosystem, Evangelism and Enablement

  Act as the voice and advocate of your workload across Everpure, partners, and the broader ecosystem. Build a strong technical community that amplifies Everpure’s message, strengthens partner capability, and drives mutual success across alliances and the channel.

  • Collaborate with alliance partners, ISVs, and GSIs to identify complementary technologies that strengthen Everpure’s workload positioning.
    
    
    
  • Leverage alliance and partner intelligence to uncover where workloads are deployed today and translate findings into actionable insights for account teams.
    
    
    
  • Lead quarterly enablement sessions and workload-focused workshops for partners, SEs, and sales teams to scale capability and readiness.
    
    
    
  • Represent Everpure at industry events, alliance webinars, and technical forums to promote Everpure’s differentiated workload strategy.
    
    
    
  • Publish technical content: blogs, demos, and videos to reinforce thought leadership and solution relevance.
    
    
    
  • Channel field intelligence, competitive insights, and feature requests to HQ via structured feedback loops and the RFE process.
  1. Operational Excellence

   

  The FSA proactively engages on key opportunities to drive technical wins and contribute to solution design in strategic deals, participating in regional deal reviews when aligned to their solution domain. Operational excellence is measured through consistent execution, data hygiene, and active field leadership that directly supports technical wins and workload growth.

  The role is accountable for maintaining clear, timely, and accurate SFDC updates, including opportunity details and specialist notes, for all engagements. These activities are measured and reviewed as part of the FSA’s overall performance to ensure sustained pipeline quality, execution discipline, and scalable success.

  Activities:

  • Maintain accurate, complete, and timely updates in SFDC for all engaged opportunities, including clear Specialist Notes, to ensure visibility, forecasting accuracy, and execution alignment.
    
    
    
  • Capture and document customer win stories tied to the solution domain on a quarterly basis, highlighting business value, technical differentiation, and repeatable success patterns.

WHAT YOU BRING 

• • Must be fluent in Japanese and proficient in English.
  • Advanced degree in computer science, engineering or mathematics
  • 10+ years’ experience with AI/ML systems across various aspects including LLMs, distributed training and inference optimization, data modelling, HPC, and/or cloud Infrastructure with special emphasis in areas of Compute, Storage, and Networking
  • Proficiency with PyTorch, Ray, Kubernetes, and GPU clusters (NVIDIA/AMD)
    Highly Motivated/Independent and self-starting
  • An outside the box thinker who can think innovatively
  • The ability to quickly dig in to learn and adapt to new technologies
  • Produce solution collateral for customers in the form of presentations, short papers, demos, Proof of concepts and
  • Create public content such as blogs, webinars or podcasts to drive thought leadership
  • Willingness to promote a culture of collaboration by partnering with solution stakeholders across the organization – eg. sales, alliance, marketing
  • A strong desire to mentor and coach team members throughout the organization.
  • Strong problem-solving skills
  • Must be able to communicate effectively and in a constructive manner with management, peers, coworkers as well as customers, partners and key industry stakeholders

   Preferred Qualifications

  • Experienced selling complicated technical solutions to customers.
  • Experience with high-performance storage technologies and data platforms

    (e.g.Kafka, Spark).

#LI-ONSITE

The Role 

As a ML Engineer within the Application Engineering team, you’ll lead critical initiatives that push the frontier of model-based autonomous driving—both in terms of core driving performance and feature-level intelligence such as personalization, comfort, and collaboration.

You’ll design and deliver ML-driven behaviours that scale from assisted to autonomous driving. Your work will span across model architecture, data pipelines, evaluation frameworks, and real-world deployment. You’ll collaborate deeply with AI Platform, Simulation, Robot SW and Model Release teams to build systems that are performant, adaptable, and ready for production.

What You’ll Be Working On

• Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization.
• Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment.
• Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness.
• Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development.
• Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems.
• Collaborate cross-functionally across various teams to ensure integration and iteration velocity.
• Mentor senior engineers and shape the long-term technical direction across Autonomy.
  
  

About you  

Essential 

• Extensive and proven track record of shipping deep learning systems to production.
• Expert in deep learning (esp. sequential models, control, planning, or perception).
• Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.
• Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components.
• Ability to lead technical initiatives across teams, drive alignment, and mentor engineers.

Desirable 

• Prior work in autonomous driving, imitation learning, or trajectory prediction.
• Familiarity with personalization, human behavior modelling, or driver intent inference.
• Experience integrating ML systems into production hardware or multi-agent simulation.
  
  

This is a full-time role based in our office in Japan.  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.  

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

Open to overseas candidates/Visa Support

This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.

What You’ll Work On

• Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
• Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
• Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
• Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).

What We’re Looking For

• Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
• 4+ years of industry experience in ad tech, with a focus on performance optimization.
• Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
• Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
• Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).

#LI-AK1

About Appier 

Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.

About the role

AI is reshaping how brands connect with consumers — and at Appier, we’re at the forefront. Our Playable Ads team builds AI-powered ad experiences — from interactive playable formats to video ads — that drive dramatically higher engagement and conversion for the world’s leading apps and games. We’re looking for a Senior Machine Learning Scientist to push the boundaries of what’s possible — applying cutting-edge ML, generative AI, and optimization techniques to create smarter, more compelling ad creatives at scale.

If you’re excited about turning the latest advances in AI into products that reach millions of users, and you thrive at the intersection of research and real-world impact, we’d love to talk.

What You’ll Work On

• Apply ML and generative AI techniques to problems such as creative optimization, user behavior prediction, engagement modeling, and dynamic content generation for various creative formats.
• Own the end-to-end ML lifecycle — from problem framing and experimentation through to production deployment and continuous improvement.
• Collaborate closely with product, engineering, and design teams to translate business goals into well-defined ML solutions.
• Conduct offline and online evaluation, A/B testing, and performance monitoring to continuously improve model quality and business impact.
• Stay current with the latest research in areas like LLMs, multimodal models, reinforcement learning, and recommendation systems, and proactively propose innovative applications to the team.
• Mentor fellow scientists and contribute to the team’s technical standards and culture.

What We’re Looking For

[Minimum qualifications]

• Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a related field.
• Solid understanding of modern ML models and algorithms, with hands-on experience in at least one area such as prediction/optimization, generative models, recommendation systems, computer vision, or reinforcement learning.
• Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
• Practical experience taking ML models from prototype to production, including pipeline development and performance monitoring.
• Strong analytical and problem-solving skills with the ability to diagnose model behavior and improve training pipelines.
• Clear communicator who can explain technical ideas to both technical and non-technical stakeholders and enjoys working in a fast-paced, collaborative environment.
• Proficient in using LLM-powered development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to accelerate productivity.
• Ability to balance cutting-edge research with time-to-market constraints, delivering iterative PoCs that validate product hypotheses and translate into production-ready solutions.

[Preferred qualifications]

• Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, KDD, RecSys).
• Experience in the advertising technology or MarTech domain.
• Contributions to open-source projects or active involvement in research communities.

#LI-AK1

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

Open to overseas candidates/Visa Support

This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

Our engineering team has a solid technical background, which would be a great environment for a skilled engineer.

In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.

What You’ll Work On

• Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
• Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
• Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
• Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).

What We’re Looking For

• Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
• 5+ years of industry experience in ad tech, with a focus on performance optimization.
• Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
• Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
• Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).

Language

Fluent in English or Chinese.

#LI-AK1

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.

What You’ll Work On

• Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
• Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
• Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
• Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).

What We’re Looking For

• Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
• 4+ years of industry experience in ad tech, with a focus on performance optimization.
• Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
• Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
• Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).

#LI-AK1

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you’ll build identify graph to enrich unified customer profile and also identify high purchase value users to drive ROAS by machine learning model.

What You’ll Work On

• Leverage scientific methods to build identify graph and identify high-value users
• Drive online experiments to continuously improve ROAS
• Own the project independently.
• Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of industry experience on identify graph, ID mapping and cross-device mapping in digital Ads related fields, and generate mapping and profile under large-scale data.
• Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

#LI-AK1

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

Open to overseas candidates/Visa Support

This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you'll measure ads incrementality on different type of traffic, creative, users, and also improve campaign efficiency on combination having good incrementality by machine learning model and AI automation.

What You’ll Work On

• Leverage scientific methods to improve ads measurement.
• Drive online experiments to continuously improve ads effectiveness.
• Own the project independently.
• Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, Econometrics, or related field.
• 3+ years of industry experience on causal inference, incrementality, marketing mix modeling or other measurement solutions on digital Ads related fields, and understand the assumption and difference across methods.
• Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

Language

Fluent in English or Chinese.

#LI-AK1

About the role 

We are seeking an experienced Machine Learning Lead to helm our Machine Learning team. 

In this pivotal role, you will be the engineering architect behind Vulcan’s core AI capabilities. You will act as the nexus between Research, Platform, and Product. Your mission is to translate cutting-edge findings on GenAI threats into robust, production-ready machine learning models that power our GenAI Security Guardrails (Blue Team) and Automated Vulnerability Assessment (Red Team). 

Crucially, you will serve as the bridge between deep tech and business strategy, articulating technical constraints (like FLOPS and latency) to leadership and clients while guiding the engineering direction. 

Key Responsibilities

1. Model Development & Optimization (Training & Fine-tuning):

• Research to Production: Collaborate with the Security Research Team to operationalize new threat detection techniques. They identify the "what" (e.g., new prompt injection patterns); you determine the "how" (model architecture, training strategy). 
• Fine-tuning & Adaptation: Lead the fine-tuning of Language Models (e.g., using LoRA/PEFT) to optimize for our supported muti-lingual languages and specific security intents.
• Multimodal Readiness: Prepare the system for Multimodal (Text + Image/Audio) capabilities. Evaluate and implement models to detect visual prompt injections and non-textual threats as the product evolves. 

2. MLOps& Data Infrastructure: 

• Enhance & Scale MLOps: Take ownership of our existing ML pipelines. Focus on optimizing and scaling CI/CD/CT workflows to improve training efficiency and deployment velocity. 
• Data Governance: Implement and enforce rigorous Data Versioning strategies (e.g., DVC) to ensure complete reproducibility of model artifacts and datasets.
• Monitoring & Reliability: Maintain rigorous monitoring for model drift and performance, ensuring high reliability in a production security environment.

3. Cross-Functional Implementation & Leadership:

• Platform Collaboration: Work closely with the Platform Engineering Team to integrate ML models into the broader product architecture. Ensure seamless interaction between model inference services and the main platform logic. 
• Team Leadership: Lead and mentor Machine Learning Engineers, fostering a culture of engineering rigor, code quality, and operational excellence.
• Resource Management: Manage GPU resources and compute budgets effectively for both training and inference workloads. 

4. Technical Strategy & Stakeholder Management:

• Translating Tech to Business: Act as the technical voice of the ML team. You must effectively explain complex ML concepts (e.g., FLOPS, quantization trade-offs, model latency vs. accuracy) to executive leadership and clients. 
• Cost-Benefit Analysis: Justify compute resource investments. Articulate the trade-off between infrastructure costs (GPU hours) and performance gains to non-technical stakeholders. 

Qualifications

• Experience: 5+ years in Machine Learning Engineering, with specific experience in leading technical projects or mentoring engineers.
• Communication & Business Acumen: Exceptional ability to distill complex technical topics (e.g., compute complexity, infrastructure costs) into clear, business-relevant insights for decision-makers.
• MLOps Proficiency: Proven experience in optimizing ML pipelines and infrastructure. Familiarity with tools like MLflow, Kubeflow, Airflow, and Data Versioning tools (DVC, etc.).
• Engineering First: Proficient in Python, Docker, and Kubernetes. You treat ML models as software artifacts that need testing and version control.
• NLP & LLM Expertise: Experience with Transformer architectures, Embeddings, and LLM fine-tuning. Familiarity with frameworks like PyTorch, Hugging Face, and vLLM.
• Language Support: Experience processing or fine-tuning models for multi-lingual environments. 

Nice to Have

• Multimodal Expertise: Experience working with Multimodal models (Image-to-Text, Text-to-Image, VLMs like CLIP, LLaVA).
• Security Awareness: Understanding of GenAI security threats (e.g., Prompt Injection).
• High-Performance Computing: Experience optimizing inference speed (quantization, distillation, vLLM) for real-time applications.
• Vector Database: Experience with Vector DBs for RAG applications. 

Why Join Us? 

• Innovative Environment: Be part of a company at the forefront of technology to provide security in GenAI, with opportunities to work on groundbreaking projects. 
• Growth Opportunities: Take your career to new heights with our career development programs and growth-focused culture. 
• Dynamic Team: Join a multi-cultural and dynamic team of dedicated professionals who inspire and support each other. 
• Compensation: Competitive salary and benefits package, commensurate with experience and performance. 

Application Process 

• If you're ready to embark on this exciting journey and contribute to shaping the future of GenAI security, please submit your resume outlining your relevant experience and motivation for applying.
• If you prefer a direct connection or have specific questions about our vision, feel free to reach out to our Co-founder, Alvin Kwock, via LinkedIn.