ML Ops Engineer

Insight Global is actively hiring a ML Ops Engineer in support of a newly awarded Government Program in Woodlawn Maryland. The selected candidate will work on a team responsible for automating and deploying ML models into a production environment. The selected candidate should have senior level experience in Python, and have experience managing and deploying custom built applications. Experience with ML Frameworks such as Tensorflow, Pytorch, Scikit, Panda and Sagemaker.

Insight Global expects to pay 140k - 150K depending on experience.

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Masters +5 years of experience or Bachelor's Degree + 7 years of experience
Understanding ML development lifecycle (labeling, training, testing, deployment, monitoring)
Experience deploying high throughput ML models to a production environment. In particular, managing and deploying custom built applications (e.g. with limited to no use of Docker containers)
Expert in Python and dev/test/prod deployment pipelines
Requires proficiency in:
Java
Query languages such as SQL (PostgreSQL) and NoSQL (MongoDB)
Other programming concepts and tools such as regular expressions and version control (Git)
Experience managing ML model performance, such as memory management and debugging
Experience with ML frameworks: Tensorflow, Pytorch, ONNX, Scikit-Learn, Pandas, Keras, Tesseract, Sagemaker, AWS++6

Experience with NLP and ML technologies and concepts such as: BERT, CNN, RNN, SVMs, k-Nearest Neighbors, Linear/Logistic Regression and Classification, Ensemble Methods, Graphical Models, Clustering, MLPs, Transformers, N-gram, Skipgram
Knowledge of and experience using various NLP approaches, particularly:
NLP preprocessing steps such as tokenization and vectorization
Pattern recognition/feature extraction (N-Gram, Skipgram, etc.)
Supervised, Unsupervised, and Semi-Supervised learning techniques
Practical experience leveraging open source libraries for emerging approaches to NLP
Chunking/Tokenization
Semantic parsing
Information extraction
Experience building, deploying, and maintaining infrastructure and pipelines for LLMs.
Experience integrating prompt management into pipelines.
Understanding of challenges such as token usage, cost, hallucination rates.

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.