Sr Machine Learning Engineer
Sr Machine Learning Engineer
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1 Vacancy
Job Description
Sr. Machine Learning Engineer
Clearance Level: Top Secret (TS/SCI Eligible)
US Citizenship: Required
Job Classification: Full Time
Location: Remote
Years of Experience: 7 10 years
Education Level: Bachelors Degree or equivalent experience
What Makes this a Great Opportunity:
An exciting remote telework opportunity to work as a Sr. Machine Learning (ML) Engineer who will be responsible for research development implementing and deploying machine learning models and algorithms to solve a wide range of cyber analytical challenges. You will collaborate with crossfunctional teams to identify opportunities for applying machine learning techniques collect and preprocess data design and train models and deploy solutions into production environments. This role offers an exciting opportunity to work with stateoftheart technologies and make a significant impact in the field of machine learning.
Position Description:
We are looking for a Machine Learning (ML) Engineer with documented expertise to be responsible for researching developing architecting and integrating ML models algorithms tools and techniques into existing or new environments. A candidate who will architect and implement machine learning and extracttransformload (ETL) algorithms and conduct data integrity and validation actions. A candidate who will work with our data scientists to design develop and integrate ML models and algorithms to address specific problems (e.g. classification regression clustering recommendation systems etc. and introduce ML and pattern recognition to discover hidden insights. Successful candidates for this role must have critical thinking skills be creative curious resourceful and have a passion for conveying a wide range of information through research leading to deeper insights. The candidate may work independently but participate in projectwide reviews of requirements system architecture and detailed design documents. Our ML Engineer must collaborate well with a strong leanforward attitude to shift knowledge left deliver well and produce quality results.
- Ability/experience to research and develop algorithms to analyze structured cybersecurity data including supervised machine learning entity resolution classification and the implementation of analytical algorithms on a distributed cloudbased infrastructure.
- Assist and introduce ML and pattern recognition to discover hidden insights; architect and implement data processing cleansing and conducting data integrity and validation actions.
- Exercise creativity in applying nontraditional approaches to the analysis of unstructured data in support of highvalue use cases using multidimensional visualization.
- Implement processing on highvolume highvelocity data streams.
- Requires strong technical and computational skills engineering physics and mathematics coupled with the ability to code design develop and deploy sophisticated applications using advanced structured data analysis techniques and utilizing highperformance computing environments.
- Can utilize advanced tools and computational skills to interpret connect predict and make discoveries in complex cybersecurity data and deliver recommendations for business and analytic decisions.
- Recommend and implement interactive reports visual analytics and dashboards focused primarily on understanding and using deep packet inspection of structured and unstructured collected digital data.
- Work closely with data scientists software developers and project managers to understand requirements and identify opportunities for applying data analysis techniques.
- Collect preprocess and analyze large datasets to extract meaningful insights and features for model training.
- Collaborate with software developers to integrate data analytical solutions into production systems and applications.
- Stay updated on the latest advancements in large data analytics and machine learning research and technologies and identify opportunities for innovation and improvement.
- Demonstrate ability to research and apply new tools techniques and solution approaches. Continually learn and improve your skills through sharing with others and taking advantage of available training sources.
Required Skills:
- Experience working with machine learning data science or related fields.
- Experience working with cybersecurity data.
- Experience in statistical analysis and visualization of complex data.
- An understanding and ability to implement data hygiene methods via ETL.
- Ability to build upon previous analytics capabilities to enable more complex analysis of large datasets including graphs to generate actionable intelligence.
- Solid understanding of machine learning algorithms and techniques including supervised and unsupervised learning deep learning reinforcement learning etc.
- Handson experience with popular machine learning libraries and frameworks (e.g. TensorFlow PyTorch Scikitlearn Keras SciPy etc..
- Experience with data processing and analysis tools (e.g. Python SciKit NumPy SQL Spark etc..
- Excellent problemsolving and analytical skills with a keen attention to detail.
- Strong communication and collaboration skills with the ability to independently or to work effectively in a team environment; the ability to quickly adapt to changing priorities/requirements.
- Experience with network traffic inspection tools (e.g. Suricata Arkime Zeek etc..
Desired Skills:
- Experience with Apache Spark Apache Streaming and Jupyter Hub Event Reporter to introduce ML and pattern recognition to discover hidden insights.
- Working knowledge of networks network traffic data and virtual environments.
- Experience with containerization (e.g. Docker Kubernetes Rancher etc..
- Experience with ML methods (e.g. decision trees neural networks reinforcement learning etc..
- An understanding and working knowledge to analyze and gain visibility to network metadata and content identify malicious code anomaly detection and potentially predictive analysis.
- Working knowledge in programming languages (e.g. Python Rust Go Java etc..
- Working knowledge with cloud computing platforms (e.g. AWS Azure or Google Cloud etc..
- Familiarity with big data technologies (e.g. Elastic Search Apache Hadoop Spark Kafka etc..
- Experience deploying ML models in production environments using containerization technologies (e.g. Docker Kubernetes).
- Publications or contributions to MLrelated research projects or opensource initiatives.
Required Experience:
Senior IC
Employment Type
Full-Time
