At a Glance
- Tasks: Lead a team to design and deliver cutting-edge ML infrastructure from backend to frontend.
- Company: Join Parser, a forward-thinking tech company in London.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on best practices in ML deployment.
- Why this job: Make a real impact by guiding innovative ML projects and collaborating with talented data scientists.
- Qualifications: Strong MLOps experience and leadership skills required.
The predicted salary is between 75600 - 92400 £ per year.
Parser in London is seeking a Tech Lead with a strong MLOps background to design and deliver ML infrastructure, owning the end-to-end stack from backend to frontend while guiding a 5+ engineer team. You will collaborate with data scientists and cross‑functional stakeholders to deploy scalable ML systems, migrate from MLflow to AWS SageMaker, and enforce best-practice MLOps across training, serving, monitoring and deployment.
Senior MLOps Tech Lead — End-to-End ML Infra & Frontend in London employer: Parser
Parser is an exceptional employer that champions a culture of innovation and collaboration, offering Senior Java Engineers the chance to work on impactful projects in a fast-growing, multicultural environment. With a hybrid working model based in the UK, employees benefit from competitive compensation, medical insurance, and opportunities for continuous learning alongside top-tier specialists. Join us to take ownership of your work and contribute to meaningful digital transformations while enjoying a flexible work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps Tech Lead — End-to-End ML Infra & Frontend in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Parser!
✨Show Off Your Projects
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✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Parser.
✨Apply Directly through Our Website
When you find a suitable opening like Senior MLOps Tech Lead — End-to-End ML Infra & Frontend at Parser, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior MLOps Tech Lead — End-to-End ML Infra & Frontend in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Parser, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Parser. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Parser
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Parser!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
