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- Tasks: Build a top-notch data operations environment and manage the data lifecycle in production.
- Company: Join Palabra.ai, the world's first real-time voice translator for apps like Zoom and Google Meets.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make an impact by working on innovative technology that supports over 30 languages.
- Qualifications: 5+ years in MLOps/Data Engineering with skills in Docker and CI/CD.
- Other info: Dynamic team environment with a focus on scalable solutions and cloud infrastructure.
The predicted salary is between 54000 - 84000 Β£ per year.
Overview
ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ ΡΠΎΠΊΡΡ ΡΡΠΎΠΉ ΡΠΎΠ»ΠΈ β ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ ΠΏΠ΅ΡΠ²ΠΎΠΊΠ»Π°ΡΡΠ½ΠΎΠΉ data-ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΡΠ΅Π΄Ρ, Π²Π΅ΡΡ ΠΆΠΈΠ·Π½Π΅Π½Π½ΡΠΉ ΡΠΈΠΊΠ» Π΄Π°Π½Π½ΡΡ Π² ΠΏΡΠΎΠ΄Π°ΠΊΡΠ΅Π½Π΅.
Palabra.ai β ΠΏΠ΅ΡΠ²ΡΠΉ Π² ΠΌΠΈΡΠ΅ ΡΠΈΠ°Π»ΡΠ°ΠΉΠΌ Π³ΠΎΠ»ΠΎΡΠΎΠ²ΠΎΠΉ ΠΏΠ΅ΡΠ΅Π²ΠΎΠ΄ΡΠΈΠΊ, ΡΠ°Π±ΠΎΡΠ°ΡΡΠΈΠΉ Π² ΡΡΠΎΡΠΎΠ½Π½ΠΈΡ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡΡ ΡΠΈΠΏΠ° Zoom ΠΈ Google Meets. Π‘Π΅ΠΉΡΠ°Ρ ΡΠ΅ΡΠ²ΠΈΡ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΈΠ²Π°Π΅Ρ Π±ΠΎΠ»ΡΡΠ΅ 30 ΡΠ·ΡΠΊΠΎΠ², ΡΠΌΠ΅Π΅Ρ ΡΠΎΡ ΡΠ°Π½ΡΡΡ ΡΠΌΠΎΡΠΈΠΈ ΠΈ ΠΈΠ½ΡΠΎΠ½Π°ΡΠΈΠΈ ΡΠΏΠΈΠΊΠ΅ΡΠ°.
Responsibilities
- ΠΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ data-ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΡΠ΅Π΄Ρ ΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΠ΅ ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Π° Π΄Π°Π½Π½ΡΡ Π² ΠΏΡΠΎΠ΄Π°ΠΊΡΠ΅Π½Π΅.
Qualifications
- 5+ Π»Π΅Ρ ΠΎΠΏΡΡΠ° Ρ ΡΠΈΠ»ΡΠ½ΡΠΌ Π±ΡΠΊΠ³ΡΠ°ΡΠ½Π΄ΠΎΠΌ Π² MLOps/Data Engineering
- Π£ΠΌΠ΅Π½ΠΈΠ΅ ΠΏΡΠ΅Π²ΡΠ°ΡΠ°ΡΡ ML-ΠΊΠΎΠ΄ Π² ΠΏΡΠΎΠ΄Π°ΠΊΡΠ½-ΡΠ΅ΡΠ²ΠΈΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ Docker ΠΈ CI/CD
- Π‘ΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΡ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°ΡΡ ΠΌΠ°ΡΡΡΠ°Π±ΠΈΡΡΠ΅ΠΌΡΠ΅ ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ Ρ ΠΎΡΡΠ»Π΅ΠΆΠΈΠ²Π°Π½ΠΈΠ΅ΠΌ lineage
- ΠΠ»ΡΠ±ΠΎΠΊΠΎΠ΅ ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΎΠ±Π»Π°ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΡ, Π²ΠΊΠ»ΡΡΠ°Ρ Kubernetes, IAM, autoscaling ΠΈ ephemeral-ΠΈΠ½ΡΡΠ°Π½ΡΡ
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Senior Data Infrastructure & MLOps Engineer employer: Open Data Science
Contact Detail:
Open Data Science Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Senior Data Infrastructure & MLOps Engineer
β¨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes itβs not just what you know, but who you know that can land you that dream job.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects and data pipelines. We love seeing real-world applications of your work, so make sure to highlight your achievements and the impact they had.
β¨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with Docker, CI/CD, and cloud infrastructure. We want to see how you can bring your expertise to our team.
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets seen by the right people. Plus, weβre always on the lookout for passionate candidates who are eager to join us in building top-notch data operations.
We think you need these skills to ace Senior Data Infrastructure & MLOps Engineer
Some tips for your application π«‘
Tailor Your CV: Make sure your CV is tailored to the Senior Data Infrastructure & MLOps Engineer role. Highlight your experience with MLOps and data engineering, and donβt forget to mention any relevant projects that showcase your skills in building scalable pipelines and production services.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why youβre passionate about data operations and how your background aligns with our mission at Palabra.ai. Be sure to mention specific technologies youβve worked with, like Docker and Kubernetes.
Showcase Your Achievements: When detailing your experience, focus on your achievements rather than just listing responsibilities. Use metrics where possible to demonstrate the impact of your work, such as improvements in efficiency or scalability in previous roles.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. Itβs super easy, and youβll be able to upload your CV and cover letter directly. Plus, it shows us youβre genuinely interested in joining our team!
How to prepare for a job interview at Open Data Science
β¨Know Your Tech Stack
Make sure youβre well-versed in the technologies mentioned in the job description, like Docker, CI/CD, and Kubernetes. Brush up on your knowledge of data pipelines and how to track lineage, as these are crucial for the role.
β¨Showcase Your Experience
Prepare specific examples from your past work that demonstrate your 5+ years of experience in MLOps and Data Engineering. Be ready to discuss how you've turned ML code into production services and the challenges you faced along the way.
β¨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the companyβs data operations environment and how they handle scaling and cloud infrastructure. This shows your genuine interest and helps you assess if itβs the right fit for you.
β¨Demonstrate Problem-Solving Skills
Be prepared to tackle hypothetical scenarios or technical problems during the interview. Think aloud as you work through your thought process, showcasing your analytical skills and ability to design scalable solutions.
