At a Glance
- Tasks: Deploy cutting-edge ML/LLM models and collaborate with top experts in a fast-paced startup.
- Company: Join the biggest Quantum Software company in the EU, renowned for AI innovation.
- Benefits: Competitive salary, unique bonuses, relocation package, and flexible working hours.
- Why this job: Make an impact in deep tech while working with generative AI and Fortune Global 500 clients.
- Qualifications: 4+ years in MLOps with expertise in cloud platforms and programming languages like Python.
- Other info: Experience a multicultural environment with excellent career growth opportunities.
The predicted salary is between 44000 - 66000 Β£ per year.
At RemoteStar, we\βre currently hiring for one of our client based in Spain
About client
Well-funded and fast-growing deep-tech company founded in 2019. We are the biggest Quantum Software company in the EU. They are also one of the 100 most promising companies in AI in the world (according to CB Insights, 2023) with 150+ employees and growing, fully multicultural and international.
Required Qualifications
- Bachelor\βs or master\βs degree in computer science, Engineering, or a related field.
- Mid or Senior: 4+ years of experience as an ML/LLM engineer in public cloud platforms.
- Proven experience in MLOps, LLMOps, or related roles, with hands-on experience in managing machine/deep learning and large language model pipelines from development to deployment and monitoring.
- Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering.
- Expertise in model parallelism in model training and serving, and data parallelism/hyperparameter tuning.
- Proficiency in programming languages such as Python, distributed computing tools such as Ray, model parallelism frameworks such as DeepSpeed, Fully Sharded Data Parallel (FSDP), or Megatron LM.
- Expertise in with generative AI applications and domains, including content creation, data augmentation, and style transfer.
- Strong understanding of Generative AI architectures and methods, such as chunking, vectorization, context-based retrieval and search, and working with Large Language Models like OpenAI GPT 3.5/4.0, Llama2, Llama3, Mistral, etc.
- Experience with Azure Machine Learning, Azure Kubernetes Service, Azure CycleCloud, Azure Managed Lustre.
- Experience with Perfect English, Spanish is a plus.
- Great communication skills and a passion for working collaboratively in an international environment.
Preferred Qualifications
- Experience in training βMixture-of-Experts\β
- Experience working with different public cloud providers and hybrid environments.
- Experience in real-time streaming applications.
- Experience with training pipeline optimization, inference optimization, LLM observability and LLM API management
As a MLOps Engineer, you will
- Deploy cutting-edge ML/LLMs models to Fortune Global 500 clients.
- Join a world-class team of Quantum experts with an extensive track record in both academia and industry.
- Collaborate with the founding team in a fast-paced startup environment.
- Design, develop, and implement Machine Learning (ML) and Large Language Model (LLM) pipelines, encompassing data acquisition, preprocessing, model training and tuning, deployment, and monitoring.
- Employ automation tools such as GitOps, CI/CD pipelines, and containerization technologies (Docker, Kubernetes) to enhance ML/LLM processes throughout the Large Language Model lifecycle.
- Establish and maintain comprehensive monitoring and alerting systems to track Large Language Model performance, detect data drift, and monitor key metrics, proactively addressing any issues.
- Conduct truth analysis to evaluate the accuracy and effectiveness of Large Language Model outputs against known, accurate data.
- Collaborate closely with Product and DevOps teams and Generative AI researchers to optimize model performance and resource utilization.
- Manage and maintain cloud infrastructure (e.g., AWS, Azure) for Large Language Model workloads, ensuring both cost-efficiency and scalability.
- Stay updated with the latest developments in ML/LLM Ops, integrating these advancements into generative AI platforms and processes.
- Communicate effectively with both technical and non-technical stakeholders, providing updates on Large Language Model performance and status.
We offer
- Competitive annual salary starting from β¬55,000, based on experience and qualifications.
- Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.
- Relocation package (if applicable).
- Up to 9-month contract, ending on June 2026.
- Hybrid role and flexible working hours.
- Be part of a fast-scaling Series B company at the forefront of deep tech.
- Equal pay guaranteed.
- International exposure in a multicultural, cutting-edge environment.
#J-18808-Ljbffr
MLOps Engineer (Madrid, Spain) employer: RemoteStar
Contact Detail:
RemoteStar Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land MLOps Engineer (Madrid, Spain)
β¨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving cloud platforms and generative AI. This will give potential employers a taste of what you can bring to the table.
β¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to MLOps and be ready to discuss your past experiences in detail.
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace MLOps Engineer (Madrid, Spain)
Some tips for your application π«‘
Tailor Your CV: Make sure your CV is tailored to the MLOps Engineer role. Highlight your experience with ML/LLM pipelines and cloud platforms like AWS or Azure. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for generative AI and how your background makes you a great fit for our team. Let us know why you're excited about working in a multicultural environment.
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's model training or deployment, we love seeing real-world applications of your skills. It helps us understand your hands-on experience.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. Itβs the best way for us to keep track of your application and ensure it gets the attention it deserves. We canβt wait to hear from you!
How to prepare for a job interview at RemoteStar
β¨Know Your Tech Inside Out
Make sure youβre well-versed in the specific technologies mentioned in the job description, like AWS, Azure, and Python. Brush up on your knowledge of MLOps and LLMOps, as well as any frameworks like DeepSpeed or Megatron LM. Being able to discuss these confidently will show that you're the right fit for the role.
β¨Showcase Your Experience
Prepare to share concrete examples from your past work that demonstrate your hands-on experience with ML pipelines and cloud platforms. Think about specific projects where you managed model training, deployment, or monitoring, and be ready to explain your role and the impact of your contributions.
β¨Communicate Clearly
Since this role involves collaboration with both technical and non-technical teams, practice explaining complex concepts in simple terms. This will not only help you connect with your interviewers but also showcase your communication skills, which are crucial in a multicultural environment.
β¨Stay Updated on Industry Trends
Familiarise yourself with the latest advancements in generative AI and MLOps. Being able to discuss recent developments or trends during your interview can set you apart and demonstrate your passion for the field. It shows that youβre proactive and genuinely interested in contributing to the companyβs success.