At a Glance
- Tasks: Lead the deployment of cutting-edge machine learning solutions for enterprise clients.
- Company: Join a forward-thinking tech company focused on innovation and client success.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to influence and build relationships with top-tier clients.
- Why this job: Make a real impact by driving the adoption of advanced ML technologies.
- Qualifications: 2+ years in ML engineering or consulting, with strong technical and communication skills.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- Education: Bachelor's degree in Computer Science or a related field.
- Experience: 2+ years of experience in a technical, customer-facing role such as Forward Deployed Engineer, or as a Software/ML Engineer with consulting experience.
- ML Engineering & Training Expertise: Experience in the Machine Learning lifecycle (training, optimization, deployment), with a proven ability to lead and execute complex model deployments in production environments.
- Forward Deployed/Consulting Background: Proven track record working within or closely alongside client engineering teams to successfully deploy and integrate complex, high-performance software, involving cloud or on-premise ML workloads.
- Technical & MLOps Knowledge: Understanding of modern ML frameworks, programming languages including Python, and deployment technologies (Docker, Kubernetes, cloud services like SageMaker/Vertex AI/Azure AI).
- Value-Driven Influence: Demonstrated ability to influence senior technical leaders and lead engineers, translating complex model performance and system architectures into clear, tangible business value and deployment assurance.
What the job involves
- You will be the main technical architect responsible for how our most strategic enterprise clients and partners implement and deploy our machine learning solutions.
- As one of our first group of Forward Deployed ML Engineers, you will establish our ML solutions for organizations concerned with the quality, security, performance, and cost of coding models.
- You will leverage your deep ML expertise and technical skills to ensure successful, production-grade implementations, ultimately driving rapid market adoption through proven on-site technical success and client satisfaction.
- End-to-End Ownership: Proactively engage with client or partner teams in Research, Engineering, Data Science, MLOps, Infrastructure to understand their business and technical requirements. With our internal R&D team in the loop, design specific implementations that you will integrate, optimize, and productionize within the client’s existing or greenfield systems as well as transferring technical knowledge to client teams when applicable.
- Subject Expert: Stay up-to-date with the latest LLM capabilities and implementation patterns, you are learning driven. You will need to explain complex technical details and concepts to both technical and non-technical audiences.
- Influence Model Training & Tuning: Represent our core R&D team on-site, leading technical engagement with modern techniques covering all stages of model training using complex, proprietary client data. Ensure architecture is aligned with and optimized for specific constraints (e.g. GPU types, air-gapping).
- Develop Deployment Strategy: Define and execute a global technical strategy for integrating our ML solutions into diverse client environments, ensuring compliance with sector-specific data security standards and performance SLAs. Based on your implementations, build reusable playbooks and libraries that will accelerate yourself and others.
- Building Relationships: Operate autonomously and with agency to build strong relationships with clients, create strategic technical partnerships and drive high-value, referenceable production deployments.
- Serve as Internal Expert: Act as the primary internal consultant, advising product, research, and sales on real-world client infrastructure limitations, performance bottlenecks, and emerging technical standards necessary for product success.
Forward Deployed Engineer (Machine Learning) employer: SonarSource
As a Forward Deployed Engineer (Machine Learning) at our company, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. We offer competitive benefits, including professional development opportunities and a supportive environment that encourages personal growth, all while working with cutting-edge technology in a location that fosters creativity and engagement with industry leaders. Join us to make a meaningful impact by deploying advanced machine learning solutions for our strategic enterprise clients.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed Engineer (Machine Learning)
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's GitHub repos or a personal website, having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Prepare for those interviews! Research common questions for Forward Deployed Engineers and practice your responses. Be ready to discuss your experience with ML frameworks and how you've tackled real-world problems in past roles.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a leg up in the process, so make sure to check out our latest openings.
We think you need these skills to ace Forward Deployed Engineer (Machine Learning)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Forward Deployed Engineer role. Highlight your experience in machine learning, client-facing roles, and any relevant technical skills. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your experience makes you a perfect fit for our team. Don’t forget to mention specific projects or achievements that showcase your skills.
Showcase Your Technical Skills:In your application, be sure to highlight your expertise in ML frameworks, programming languages like Python, and deployment technologies. We love seeing candidates who can demonstrate their technical prowess and how they’ve applied it in real-world scenarios.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining the StudySmarter family!
How to prepare for a job interview at SonarSource
✨Know Your ML Stuff
Make sure you brush up on the entire machine learning lifecycle. Be ready to discuss your experience with training, optimisation, and deployment of models. They’ll want to hear about specific projects where you’ve led complex model deployments, so have those examples at the ready!
✨Understand Client Needs
Since this role involves working closely with client engineering teams, it’s crucial to demonstrate your ability to engage with clients. Prepare to share how you've successfully integrated software solutions in past roles, and think about how you can translate technical jargon into business value for non-technical stakeholders.
✨Show Off Your Technical Skills
Familiarise yourself with the modern ML frameworks and deployment technologies mentioned in the job description, like Docker and Kubernetes. Be prepared to discuss your proficiency in Python and any cloud services you've used, such as SageMaker or Azure AI. Practical examples will help solidify your expertise.
✨Build Relationships
This role is all about building strong relationships with clients. Think about how you can showcase your interpersonal skills during the interview. Share stories that highlight your ability to influence senior technical leaders and collaborate effectively with diverse teams.
