(Senior) ML Engineer

Knowit Oy; Helsinki; Hybrid; EUR 65,000 - 73,000; Full time

Benefits offered by this job

Lunch benefits

Commuting benefits

Sports & culture benefits

Extensive occupational healthcare

Accident insurance

Work equipment of your choice

Remote work from abroad

Recruitment bonuses

Sales lead bonuses

Job summary

Knowit Oy is seeking a (Senior) ML Engineer to strengthen our Data & Analytics crew. You will develop, train and deploy machine learning models and production pipelines, covering the model lifecycle from data prep to serving and monitoring.

You will collaborate with data scientists, software developers and client teams to connect ML with operational systems. Many projects involve time-series, sensor and IoT data, with use cases like anomaly detection, predictive maintenance and demand

Qualifications

• Strong Python and software engineering skills.
• Hands-on experience developing and evaluating ML models.
• Practical Azure and/or AWS experience.
• Experience taking models into production and applying MLOps practices.
• SQL and data processing skills.
• Interest in AI-assisted coding and applying good engineering judgment.

Responsibilities

• Develop, train and evaluate ML models and production pipelines.
• Build automated data prep, model training, evaluation and deployment pipelines.
• Connect ML workloads with cloud data services and event-driven architectures.
• Collaborate with data scientists, data engineers, software developers and client teams.
• Monitor model performance and data quality, diagnose drift and retrain as needed.

Skills

Python

Software engineering

ML modeling

Azure/AWS

MLOps

SQL

Finnish/English comms

Tools

Azure ML

IoT Hub

Event Hubs

Job description

We are looking for an (Senior) ML Engineer to strengthen our Data & Analytics crew. If you enjoy developing machine learning models and building the pipelines and infrastructure that make them work in production, we would like to hear from you.

What is the role about?

As an (Senior) ML Engineer at Knowit, you will develop, train and evaluate machine learning models and build the technical foundations needed to deploy and operate them. Your work will cover the model lifecycle, from preparing data and experimenting with approaches to building production pipelines, serving predictions and monitoring performance.

You will work closely with data scientists, data engineers, software developers and client teams to connect machine learning with operational systems. This could mean developing a new model or taking an existing experiment and turning it into a reliable, maintainable production service.

Many of our cases involve industrial time‑series, sensor and telemetry data, with use cases such as detecting anomalies, monitoring equipment condition and predicting failures to support maintenance decisions. The role also covers other domains, for example pricing and demand prediction.

Depending on the project, your work could include:

• Analysing business and operational data to identify and quantify the factors that drive an outcome, such as price, quality, demand or cost, and forming and testing hypotheses together with domain experts.
• Turning analysis results into clear recommendations or into predictive models and tools the client can use in their decisions.
• Preparing and processing time‑series and IoT data, building features, and developing models for predictive analytics and anomaly detection.
• Training, evaluating and improving models, choosing validation methods and metrics that reflect their intended use.
• Building automated pipelines for data preparation, training, evaluation and deployment.
• Implementing batch inference or online serving solutions and integrating predictions with operational systems.
• Connecting ML workloads with cloud data services on Azure, AWS or both, and with event‑driven architectures.
• Monitoring model performance and data quality, identifying drift, and supporting model updates and retraining.

You will help define what a successful solution looks like with the client, considering both model quality and practical requirements such as reliability, latency and business value.

You will also have opportunities to share your expertise, develop our ML practices and contribute to offering development and pre‑sales together with your colleagues.

What do we expect from you?

We are looking for an engineer with practical experience in machine learning and a strong software development foundation. You enjoy working with both models and the systems around them and take ownership of how your solutions perform in production.

The most important things you bring are:

• Strong Python and software engineering skills. You write maintainable, tested code and are comfortable with version control, APIs, integrations and building reusable components for ML systems.

• Hands‑on experience developing and evaluating ML models. You understand data preparation, feature engineering, training and validation, and can select suitable methods and metrics for the problem. You are familiar with relevant ML libraries and frameworks.

• Practical Azure and/or AWS experience. You can build and deploy ML solutions on Azure, AWS or both, and connect them with the surrounding data infrastructure. Familiarity with Azure Machine Learning and services such as IoT Hub, Event Hubs and Azure Functions is particularly relevant.

• Experience taking models into production. You understand MLOps practices, including model and experiment versioning, automated deployment, CI/CD, monitoring and evaluation. You can build pipelines and serving solutions that remain reliable and maintainable after deployment.

• SQL and data processing skills. You can work with data engineers and data scientists to connect ML development with data platforms and production systems.
• Experience with or interest in AI‑assisted coding. You are keen to use AI coding tools to support development, testing and documentation, and apply sound engineering judgment to review and validate generated code.

You can explain your technical choices clearly, clarify requirements with clients and connect model development with business goals. You also consider data security, access control and responsible use of machine learning in your work.

You communicate clearly in Finnish and/or English and enjoy developing your expertise together with others.

We also appreciate:

• Experience with time-series, sensor or IoT data. You understand the challenges of working with this data and have applied machine learning to use cases such as anomaly detection, predictive maintenance, failure prediction or condition monitoring.
• Experience with Databricks and/or Snowflake, particularly in ML and predictive analytics workflows.

• Familiarity with containerisation, infrastructure as code and cloud deployment automation.

• Experience in industrial environments or working with operational technology and processes.

• Previous consulting, pre‑sales or project delivery experience.

You do not need to bring every additional skill listed above. Strong Python, practical ML expertise and the ability to take models into production are the foundation of this role.

What do we offer you?

At Knowit, we value broad expertise as well as the willingness to explore and master new areas. We take pride in our hands‑on way of working and our deep technical expertise.

And because we don't want this to be just a one-sided wish list, we want you to have the opportunity to shape your role as an expert and take ownership of your professional development, with our support. Everyone is welcome to be their whole self at Knowit, and we consider a relaxed yet professional working community valuable in its own right.

Here is what we offer:

• A fixed monthly salary of 5800 – 6500€, depending on your skills, experience and capabilities.

• A team and community where it is easy to grow and get support when you need it. Our people are at different stages of their careers, and we offer opportunities that challenge and develop both recent graduates and more experienced professionals.

• Our People Lead model, which has received a lot of positive feedback internally. We believe that a manager's most important responsibility is to ensure that you, as an expert, have the best possible conditions to succeed in your work and develop professionally.

• Time and resources to develop your expertise during working hours, including training, certifications and guild activities. We want to invest in your professional development.

• Opportunities for internal mobility. Your work can make an impact across several industries, and working with different customers gives you genuine opportunities to learn something new.

• A technology‑independent environment. We work with modern technologies, tools and best practices, and have strong technology partnerships with major players in the industry. At the same time, we remain curious, ready to learn new things and willing to challenge the status quo.

• Flexible remote and hybrid working arrangements that adapt to different life situations.

• A excellent work‑life balance. We work on large and meaningful projects in sustainable digitalization, but we also recognize that everyone is a whole person and that there is more to everyday life than work.

• A comprehensive range of employee benefits, including lunch, commuting and sports/culture benefits, extensive occupational healthcare, accident insurance, work equipment of your choice, recruitment and sales lead bonuses, and the possibility of temporarily working remotely from abroad.