Machine Learning Engineer

W-2 Open Positions Need to be Filled Immediately. Consultant must be on our company payroll, Corp-to-Corp (C2C) is not allowed.

Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.

Candidates encouraged to apply directly using this portal. We do not accept resumes from other company / third-party recruiters.

Job Overview

Job ID : J36993

Specialized Area : Machine learning

Job Title : Machine Learning Engineer

Location : Lewisville, TX

Duration : 6 Months

Domain Exposure : Banking & Finance, Education, IT / Software

Work Authorization : Client : To Be Discussed Later

Employment Type : W-2 (Consultant must be on our company payroll. C2C is not allowed)

Responsibilities

Work with raw data (including big data). Must have knowledge of preprocessing procedures and ability to prepare data for modeling.

Experience in feature engineering.

• Develop and debug in Python, Java, C or C++. Proficient in git version control. R and Matlab are also relevant.
• Design and evaluate intrinsic and extrinsic metrics of your model's performance which are aligned with business goals.
• Define how we build and deploy systems around intelligent algorithms.
• Work with computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, Pickle, Seaborn, statsmodels, NLTK).
• Use Natural Language Processing for Name Entity Recognition, Sentiment Analysis, and topic modeling. Familiarity with Latent Dirichlet Allocation.
• Assess opportunities and develop models to support Sanctions Screening alerting and disposition decisioning.
• Innovate solutions for various sanctions screening problems.
• Build model diagnostics, choice justification paradigms, testing and training approaches.
• Apply machine learning and statistical modeling methods for supervised and unsupervised learning.
• Tune and analyze algorithms and extract actionable insights. These methods include (but are not limited to) regression analysis, clustering, outlier detection, novelty detection, decision trees, collaborative filtering, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks and deep learning, feature selection, and factorization methods.
• Effectively communicate and explain complex data products in simple terms.

Equal Opportunity Employer

ROBOTIC PROCESS AUTOMATION LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M / F / D / V).

Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship / immigration status, veteran status or any other protected status.

ROBOTIC PROCESS AUTOMATION LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters.

Nor will ROBOTIC PROCESS AUTOMATION LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.

S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract.

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