Senior Machine Learning Engineer

Responsibilities

• Exploratory data analysis.
• Development of ML algorithms.
• Deployment to millions of users.
• End-to-end ownership of ML problems for the Foundation.

Requirements

Essential:

• 4+ years of professional experience within ML field.
• Good understanding of neural networks, especially RNNs.
• Good understanding of classic ML algorithms (e.g. SVM, trees, clustering, etc.).
• Programming skills (Python is preferred).
• Experience working with big datasets (≥ 1Tb).

Nice to have:

• Experience deploying ML models to production.
• Data visualization skills.
• Knowledge of big data technologies (Redshift, HDFS / S3, Spark, Kafka / Kinesis, etc.).
• Experience in the med tech domain.

Reward

The strength of Flo is built on the capability of its talent. In recognition of this, they offer:

• Top of the market salaries.
• Career growth, progression, and promotion opportunities.
• Eligibility for annual salary increases.
• Company equity grants through Flo’s employee share option plan (ESOP) are eligible to all employees.

Flo is an international team of highly skilled top talent. We have ambitious and challenging objectives and are committed to granting our team the freedom to explore. Our core cultural values are based on engaging teamwork, continuous improvement, and smart transparency. Our mission fuels our everyday work, and we’re proud of the impact we’re making.

Build the future of women’s health with us.

Diversity statement

The strength of their workforce is in the diverse backgrounds of their employees, and Flo is committed to applying its equal opportunities policy at all stages of recruitment and selection. This means recruitment and selection of talent into Flo Health companies is only based on individual merit and qualifications directly related to professional competence.

Shortlisting, interviewing, and selection will always be carried out without regard to gender identity or expression, sexual orientation, marital or civil partnership status, color, race, nationality, ethnic or national origins, religion or beliefs, ancestry, age, veteran status, mental or physical disability, medical condition, pregnancy or maternity status, trade union membership, or any other protected characteristics.