Associate Machine Learning Engineer

Job description

Company Description

Welcome to the good side of tech 👋

You might have heard about us, but with a different name: Znanylekarz. It all started 10 years ago when we asked ourselves: is anyone in healthcare thinking about patients? We jumped in and we empowered patients by giving them access to leave and read reviews about their visit. We then provided doctors with the technology to manage bookings easily and save time, so they could devote themselves to what they always wanted: treating patients. And today is the day in which we ask you: wanna join us in the next step of making the healthcare experience more human?

Docplanner at scale

We are leaders in 13 countries so far, and more than 90 million patients trust us every month. 280.000 specialists believe in us and our product, and so do leading venture capital funds such as Point Nine Capital, Goldman Sachs Asset Management, and One Peak Partners. And yet, employing over 2.900 people all over the globe, we managed to keep the startup mindset we started with over 10 years ago.

How does Docplanner Tech fit here?

At Docplanner Tech we are a diverse group of ~325 people working in teams that include engineers, designers, product managers, data and research. We are responsible for building the product for all locations. Taking care about talent matters to us, that’s why the engineering team has an amazing balance of new team members and people that have been in DP for years.

We could tell you about us, but we will let our reviews on Glassdoor speak for themselves. In case you’d like to see how it feels to be 100% yourself at work, here’s a video of us.

And why should you join us?

Because it feels good to tell your family and your friends how you made the world a little bit better. You go to bed knowing that what you do matters, and that your talents align with your beliefs.

We want to make the healthcare experience more human, and that starts with you being you. We believe that taking the diversity of human experience into account makes a better healthcare experience for all. We’re not just different: we embrace diversity. We will encourage you to come to work your whole self, and that includes not coming to the office at all if you prefer not to, as we’re 100% remote-friendly.

Job Description

Area of Work

You will join our global Machine Learning  and Data Science unit - a core team of machine learning scientists (LLM, ASR), engineers and an expanding group of country-specific linguists - embedded in the ever growing Noa product organization used daily by doctors in Brazil, Mexico, Poland, Italy, Spain and Germany. Noa.ai’s mission is to broaden access to top-quality healthcare first by lifting administrative burdens from clinicians and, in the near future, by assuming selected medical tasks. Our most famous product is Noa Notes, which records consultations, transcribes the audio and produces a structured draft of the medical record.

By design, we operate cross-functionally, moving ideas from prototyping and rapid validation to full-scale production with state-of-the-art ML frameworks and modern MLOps practices. We begin with rapid validation sprints when engineers, product managers, and product developers work side by side on early experiments, then centralise and consolidate proven capabilities, standardizing validation methods and engineering best practices through shared tools, frameworks, and lifecycles.

Role

As a Machine Learning Engineer in the Noa ML team you will support a product area within our Noa organisation to deliver end to end ML capabilities. You will work alongside other machine learning professionals at various seniority levels and report directly into the Head of Machine Learning & Data Science.

Backed by a strong engineering culture, we pair industry-leading ML rigor with pragmatic delivery, making smart trade-offs to ship value quickly and iterate fast. In this role, you’ll work alongside exceptional engineers and scientists on one of Docplanner’s most strategic initiatives, leveraging a cutting-edge tech stack to push the boundaries of AI in healthcare.

Our tech stack includes Python, Pytorch, Whisper, FastAPI - among the others - running on Kubernetes in AWS.

What you will be doing

• Work closely with cross-functional teams, including scientists, engineers, and product stakeholders, to deliver AI-driven machine learning initiatives that directly contribute business objectives.

• Design, deploy and iterate over ML services for diverse data types (e.g., audio, text), while proactively identifying and eliminating performance bottlenecks driving continuous improvements.

• Assess platform engineering and MLOps bottlenecks; research and design scalable GPU resource-optimization strategies, and recommend solutions that balance performance, cost, and reliability.

• Research, architect, and deploy LLM-powered information retrieval solutions (eg. RAG) to deliver accurate and scalable results in complex, multilingual product environments.

• Partner with the AI Platform team to refine MLOps best practices, evolve frameworks, and establish efficient, scalable workflows.

• Architect, deploy, and maintain high-throughput, reliable data pipelines to support training-set curation and data-annotation tooling.

Qualifications

• At least one year of professional experience as an ML Engineer or Data Scientist in a fast-paced, product-driven tech environment.

• Demonstrated expertise in production-grade MLOps, leveraging, for example,  orchestration with Kubernetes, model serving via FastAPI, NVIDIA Triton and KServe, Apache Airflow for data pipelines.

• Good understanding and proficiency in deep learning frameworks such as PyTorch or TensorFlow.

• Proven ability to integrate, deploy, and optimize large language models in production-grade industry environments, ensuring scalability and robust performance. Knowledgeable in prompt engineering, basis of agent‐based workflows, and the generation and manipulation of embeddings.

• Problem-solving mindset and adaptability in dynamic environments with a focus on delivering business value to end customers.

• Proven ability to manage timelines, prioritize tasks, and deliver results under tight deadlines.

• Curiosity and eagerness to collaborate with cross-functional teams (e.g., product, marketing, engineering)

Additional Information

Let’s talk money

• A salary adequate to your experience and skills. The range is broad so that we can accommodate our roles for all levels of experience, but we will show you the career ladder to explain where we see your skills and impact within the company”. Your salary will be, now and always, 100% transparent to you;
• Flexible remuneration and benefits system via Flexoh , which includes: restaurant card, transportation card, kindergarten, and training tax savings;
• Share options plan after 6 months of working with us.

True flexibility and work-life balance

• Remote or hybrid work model with our hub in Barcelona;
• Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly);
• Summer intensive schedule during July and August (work 7 hours, finish earlier);
• 23 paid holidays, with exchangeable local bank holidays;
• Additional paid holiday on your birthday or work anniversary (you choose what you want to celebrate).

Health comes first

• Private healthcare plan with Adeslas for you and subsidized for your family (medical and dental);
• Access to hundreds of gyms for a symbolic fee in partnership for you and your family with Wellhub;
• Access to iFeel, a technological platform for mental wellness offering online psychological support and counseling.

We promote and embrace equal opportunities in our hiring process, and also every day at work. When you apply for our roles you receive equal treatment regardless of age, disabilities, gender reassignment, marital or civil partner status, pregnancy or parental status, race, colour, nationality, ethnic or national origin, religion or belief, sex, sexual orientation or any other dimension of human difference.  If you require additional support in your recruitment process, we kindly encourage you to let us know. Behind those words you’re reading, there’s a person (hi!) who already helped a candidate by adapting the interviews, and now we’re lucky to have this person with us. So, even if you’ve never asked for it before, may this serve as a sign that, now, you can do so. We can only truly be equal if we adapt to each other.

“We believe all humans, in all their beautiful diversity, should have equal rights, dignity and respect. Period.” Mariusz Gralewski,  CEO