Machine Learning Engineer

at  Fieldstream AB

ABOUT THE COMPANY:

Fieldstream is a Stockholm based AI company, operating in the marketing analytics industry. We are a small team but are growing steadily. Most employees work with tech as software developers, data engineers, ML engineers or data scientists. We are now looking for an additional machine learning engineer to join our Stockholm office.

EXPERIENCE AND SKILLS:

Professional Experience: Minimum of 3 years in machine learning engineering or related roles, with a proven track record of developing and deploying ML models.
Strong Programming Skills: Proficiency in Python and familiarity with ML libraries (e.g., TensorFlow, PyTorch).
Experience with Google Cloud: Experience with Google Cloud Platform services relevant to machine learning (e.g., Vertex AI, etc.) and deploying models in cloud environments.
Knowledge of Machine Learning Techniques: Deep understanding of various machine learning techniques and their real-world advantages/drawbacks. Specifically, experience for time series modeling is important.
Model Deployment Expertise: Experience with model deployment, A/B testing, and monitoring tools.
Data Management: Understanding of data structures, data modeling, and software architecture.
Communication: Excellent communication skills with the ability to work in a team environment and collaborate with non-technical stakeholders.
Problem-Solving: Strong problem-solving abilities with a focus on delivering business value through technology.

PREFERRED QUALIFICATIONS:

Education: Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

ABOUT THE ROLE:

As a Machine Learning Engineer at Fieldstream, you will be at the forefront of our efforts to develop, deploy, and scale machine learning models that drive our core products and services. Working closely with software- and data engineers, you will translate business challenges into data-driven solutions, leveraging our data pipelines and cloud infrastructure. Your expertise in machine learning, software engineering and data science will be pivotal in bringing innovative solutions from conception to production.

KEY RESPONSIBILITIES:

Model Development and Training: Develop, train, and validate machine learning models, utilizing data prepared by our data engineering team to address business needs and enhance product offerings.
Model Deployment and Scaling: Deploy machine learning models into production environments, ensuring they are scalable, performant, and integrate seamlessly with our existing systems.
Collaboration with Data Engineering: Work closely with data engineers to ensure a seamless data flow and efficient model training pipelines, contributing insights to enhance data preparation and pipeline development.
Performance Monitoring: Monitor model performance in production, identifying opportunities for improvement and updating models as necessary to maintain and enhance accuracy and efficiency.
Innovative Solution Exploration: Stay abreast of the latest machine learning techniques and technologies, exploring innovative solutions that can be applied to improve our products and processes.
Cross-functional Teamwork: Collaborate with product managers, software engineers, and other stakeholders to understand requirements and deliver data-driven features and improvements.
Technical Leadership: Provide mentorship and guidance to junior team members, fostering a culture of learning and innovation within the team.