Machine Learning Engineer

Description

Job Description:

Yes...a Machine Learning Engineer is needed at Leidos. Could this be you?

If you have a very strong general knowledge of packaging and deploying machine learning and artificial intelligence prototypes that contribute to making various machine learning (ML) and artificial intelligence (AI) projects ready to use in operational settings then this position could be for you. Work in our exciting Leidos AI/ML Accelerator that supports work across the entire company gaining you lots of exposure.

You have demonstrated ability working independently, as part of a technical team, and as a technical team leader. You are also an adept at researching machine learning issues and being able to apply those solution in a machine learning pipeline. In this Machine Learning position at Leidos working in our Arlington, VA. office you will use your strong Python coder with knowledge in using ML libraries, platforms, and computer architectures.

Your day to day:
- Format multimodal data for use in machine learning and design and implement machine learning pipelines using various data.
- Convert machine learning prototypes from research code to production code.
- Study and convert data science prototypes.
- Design and develop Machine Learning systems and schemes.
- Perform statistical analysis and fine-tune models using test results.
- Find available datasets online for training purposes.
- Train and re-train ML systems and models as and when necessary.
- Extend and enrich existing ML frameworks and libraries.
- Develop Machine Learning apps according to customer/client requirements.
- Research, experiment with, and implement suitable ML algorithms and tools.
- Analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by their success probability.
- Explore and visualize data for better understanding and identify differences in data distribution that could impact model performance when deploying it in real-world scenarios.

This is you:
- B.S. degree in Computer Science, Mathematics, Statistics, Machine Learning, Natural Language Processing, Artificial Intelligence, or related disciplines with 4 years of applicable experience. 4 additional years may be used in lieu of degree.
- Must be able to obtain a Top Secret security clearance with a polygraph security clearance
- Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)
- Robust data modelling and data architecture skills
- Programming experience in Python, R, Java, C++, etc.
- Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc.
- Background in constructing machine learning in the cloud (Amazon, Google, IBM, etc.)
- Expertise with the ELK Stack (Elasticsearch, Logstash, and Kibana)
- Experience in working with ML frameworks like TensorFlow and Keras
- Experience in working with various ML libraries and packages like Scikit learn, Theano, Tensorflow, Matplotlib, Caffe, etc.
- Strong written and verbal communications
- Excellent interpersonal and collaboration skills.

You will you wow us even more if you have these skills:
- Hands-on experience with Docker containerization
- Hands-on experience with Kubernetes
- Hands-on experience with Machine Learning Model Monitoring
- Hands-on experience with Dataiku
- Hands-on experience with Domino DataLab
- Hands-on experience with microservices

AIML

Pay Range:

#Remote