The machine learning engineer at Lumu Technologies is an expert in several fields of artificial intelligence, focused on extracting value from our data and turning it into direct value for our customers. The MLE will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
The MLE is a hands-on team member, heavily involved in the design and building of our data-collection architecture to ensure that solid bases are being laid for the construction of the best enterprise-level threat analytics platform in the market.
- Define, implement and improve algorithms to detect known and unknown threats using techniques in machine learning.
- Apply the latest technologies in machine learning, data mining, behavior-based analytics, and predictive analytics to correlate events through big datasets, and derive indicators of compromise.
- Examine data closely to reveal trends, patterns and actionable intelligence.
- Refining fast and big data into ‘smart data’.
- Supervising the data acquisition process.
- Finding available datasets that could be used for training and enriching our detection capabilities.
- Collaborate with the product team across several stages from the design of data-ingestion and data-transformation architecture to deploying models to production.
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
- Optimizing solutions for performance and scalability.
- Defining the preprocessing or feature engineering to be done on our data.
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.
Required Skills and Experience
- Educational background in Mathematics, Statistics, Computer Science, Information Science or Engineering
- Proven record of experience conducting Data Science projects. Experience performing investigations on large scale datasets is a big plus.
- Strong understanding of machine learning techniques and algorithms.
- Experience with common data science toolkits, such as Scikit-Learn, Pandas, R, Weka.
- Exposure to Deep Learning, or related fields.
- Competent in writing Scala, Python or Java code.
- Understanding of cybersecurity, networking traffic analysis, intrusion detection, offensive security, predictive analytics, and threat hunting is highly preferred.
- Experience with building stream-processing systems using solutions such as spark-streaming, Storm or Flink is a plus.
- Strong English verbal and written communication skills.
- Experience applying data science for Cyber Security projects is a plus.
- The ideal candidate should have a clear understanding of cyber-attacks and passion to build systems that identify, stop, and prevent those attacks.
Apply by sending your resume to: email@example.com.