**LOCATION: MEXICO REMOTE.
****How will you make an impact?
**Surrounded by collaborative colleagues, you'll have the support and opportunities that only a global leader like Thermofisher Scientific can give you.
Our respected, growing organization has an exceptional strategy for the near term and beyond.
Take your place on our strong team and help us make significant contributions to the world.Thermo Fisher Scientific's mission is to help make the world a healthier, cleaner, and safer place.
This position offers a unique opportunity to help our mission by leading and executing on our next generation scientific platform.We are looking for an ambitious, talented, and self-motivated individual, who will be a part of our data science team.
In this role you will lead a team and plan development and delivery of business requirements specified by customers.
This role requires execution as well as coordination with multiple teams to successfully deliver machine learning projects that will improve scientific data analysis.Your work will take you across many important areas of our business from experimental results to products, biological entities to laboratory techniques, and everything in between.
**Responsibilities**- Build, maintain, and improve end-to-end machine learning solutions.- Keep the ML pipelines updated with state-of-the-art ML algorithms.- Establish testing of newly developed Machine Learning models.- Work closely with Data Engineers to build pipelines that help in continuously improving models- Analyze and deliver valuable insight to customers from data.- Deploying machine learning models into production environment (on premise and Cloud).- Prototyping of valuable data-centric solutions for customers problems.- Communicate valuable information to stakeholders.- Create documentation and best practices to share with the ML community.- Manage and collaborate with a cross-functional team.
**Basic qualifications**- 3+ years' in a Machine Learning Engineer role- Hands on experience on Machine learning algorithms.- Experience deploying machine learning model on Cloud platform (such as AWS, Azure, Google Cloud)- Proficiency with languages such as Python or C#.- Proficiency using AI libraries such as Tensorflow or Pytorch.- 1+ years of experience in and productionisation of ML systems.
**Preferred qualifications**- Master's in computer science, Mathematics, or Statistics.- Experience in Machine Learning algorithm design.- 1+ year's in a Data Science Manager role.
**Applicable Keywords**: Distributed architecture, Cloud, REST, SOA, AWS, Azure, Spark, Machine Learning, Python, Tensorflow, Pytorch, MLFlow.