Back to jobs

AI/ML Engineer

Berlin · New York · London · Berlin, Germany

Pay
Pay not listed
Work setting
Remote — work setting source
Location type: Remote
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Technology — team source
Department: Technology
From the employer’s posting
Apply at Melotech

What you’ll work on

Full posting
  • Design scalable ML infrastructure and pipelines for massive media datasets

  • Fine-tune and deploy multimodal AI systems using MLOps practices

  • Optimize model performance for cost, accuracy and speed

From the employer’s posting
Designing scalable ML infrastructure and pipelines that handle massive media datasets
Fine-tuning and deploying multimodal AI systems using MLOps best practices
Optimizing model performance for cost efficiency while maintaining accuracy and speed requirements

What you’ll bring

All qualifications

Core experience

  • Degree in Computer Science, Machine Learning, Mathematics, Engineering, or related technical field
  • 3+ years of hands-on ML engineering experience building production systems at Big Tech companies, high-growth startups, or media/entertainment platforms
Qualification wording
Degree in Computer Science, Machine Learning, Mathematics, Engineering, or related technical field
3+ years of hands-on ML engineering experience building production systems at Big Tech companies, high-growth startups, or media/entertainment platforms

Tools in this posting

  • Python
  • Docker
  • Kubernetes
Source — Tool mentions in context
- 3+ years of hands-on ML engineering experience building production systems at Big Tech companies, high-growth startups, or media/entertainment platforms - Expert-level proficiency in Python, ML frameworks, and cloud platforms - Extensive experience with MLOps tools and practices including Docker, Kubernetes, model versioning, and monitoring systems
- Expert-level proficiency in Python, ML frameworks, and cloud platforms - Extensive experience with MLOps tools and practices including Docker, Kubernetes, model versioning, and monitoring systems - Proven track record deploying and scaling ML models in production environments with high availability requirements

About Melotech

Melotech is revolutionizing media and entertainment.

In the employer’s words · Read in context · Company website ↗

Posting record

Report an error

Open 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 2, 2026 · 149 days ago
Recorded sightings
49
Last seen by us
Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

Who we are

Melotech is revolutionizing media and entertainment. We create art through technology for humans to enjoy. In just 24 months, our work has been heard, watched and loved for over 4 billion minutes worldwide.

Founded by entrepreneur and investor Soheil Mirpour, Melotech has raised more than $16M from Drive Capital and Europe’s leading VCs: Cherry Ventures, Speedinvest and Global Founders Capital, alongside world-class angels from firms such as Spotify, Blackstone and KKR.

 

What you will do

As our ML Engineer, you'll be the technical backbone powering our content platform. You'll tackle the critical questions: How do we build ML systems that scale to millions of users while maintaining low latency? What's the right architecture for training and deploying models that learn from real time data? And how do we leverage cutting-edge models to enhance creative processes while preserving quality? Working fully autonomously alongside our founder and the team, your answers to these questions will directly influence our company's success. On a typical day, your tasks may include:

  • Building and deploying production ML models within our content and product ecosystem

  • Designing scalable ML infrastructure and pipelines that handle massive media datasets

  • Implementing efficient inference systems across our products

  • Fine-tuning and deploying multimodal AI systems using MLOps best practices

  • Collaborating with data science teams to transition research models into production-ready systems

  • Optimizing model performance for cost efficiency while maintaining accuracy and speed requirements

  • Integrating ML capabilities into existing platforms and building APIs for seamless model consumption

 

Who you are

You're a production-focused ML engineer who bridges the gap between cutting-edge tech and scalable systems. Your expertise lies in building robust ML infrastructure that powers real-world applications at scale. You thrive in fast-paced environments where your technical decisions directly impact business outcomes and user experiences. Typically, your profile will look like this:

  • Degree in Computer Science, Machine Learning, Mathematics, Engineering, or related technical field

  • 3+ years of hands-on ML engineering experience building production systems at Big Tech companies, high-growth startups, or media/entertainment platforms

  • Expert-level proficiency in Python, ML frameworks, and cloud platforms

  • Extensive experience with MLOps tools and practices including Docker, Kubernetes, model versioning, and monitoring systems

  • Proven track record deploying and scaling ML models in production environments with high availability requirements

  • Self-directed approach with ability to architect complex systems independently while collaborating across technical teams

  • You thrive in a fast-paced and performance-oriented environment

  • Colleagues would describe you as hard-working, ambitious and persistent

  • You're obsessed with music, video or social media

 

What makes this exciting

You are one of the first employees of an ambitious team, changing the world of media and entertainment. Being early means every decision you make shapes our trajectory. You're not a cog in the machine but the captain of your own ship, rewarded for performance and respected for leadership. Flat hierarchies mean that your voice matters, your ideas get implemented, and your impact is immediate.

We pay competitive salaries and make you an owner of the business with equity. We work remotely to give you complete freedom over your life, while meeting regularly around the world for global offsites where we strategize, bond, and push boundaries together.

 

What the process will look like

We hire on a rolling basis. Earliest starting date is always ASAP.

Once you begin our process, you can progress from start to offer within a week, depending on how quickly you can move through each stage:

  1. Take-home case study: Real-world project - showcase your skills and working style

  2. Case interview: 90-minute case discussion - getting to know you & present and debate your results with a team member

  3. Online assessment: Motivational questionnaire and aptitude test - are you made for the job?

  4. Founder interview: 90-minute interview with our CEO - going deep on all topics

  5. Team interview: Individual or group interview with other team members - depending on position

  6. Offer, contract signing and onboarding


Note: As we are still in stealth, you will learn more about Melotech as you progress through the stages. By the end of the Founder interview, you will have a full grasp of our business and the details of your role.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Berlin, Germany

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.