Industrial Engineer (17-2112.00)

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Location: 99 S Almaden Blvd., Suite 600, San Jose, CA, 95113, United States of America 

MATRIXELLENT INC. seeks to temporarily employ a work authorized individual under the H-1B nonimmigrant classification for specialty occupations. The H-1B program allows MATRIXELLENT INC., a U.S. employer, to temporarily employ a qualified nonimmigrant worker in a position that requires both (a) the theoretical and practical application of a body of highly specialized knowledge and (b) the attainment of a bachelor's or higher degree in the specific specialty (or its equivalent) as a minimum prerequisite for entry into the position.

MATRIXELLENT INC., the Petitioner, bears the burden of proof to demonstrate eligibility by a preponderance of the evidence. Matter of Chawathe, 25 I&N Dec. 369, 375-76 (AAO 2010). MATRIXELLENT INC., the Petitioner, requires an individual with a Master's degree in Industrial Engineering & Operations Research.

MATRIXELLENT INC. is defined as a tax exempt organization under the Internal Revenue Code of 1986, section 501(c)(3), (c)(4) or (c)(6), 26 U.S.C. 501(c)(3), (c)(4) or (c)(6)(8 CFR 214.2(h)(19)(iv)(A)), and has been approved as a tax exempt organization for research or educational purposes by the Internal Revenue Service (8 CFR 214.2(h)(19)(iv)(B)) to conduct scientific research for the purpose of aiding in the scientific education of college or university students (26 CFR 1.501(c)(3)-1(d)(5)(iii)(c)(1))

MATRIXELLENT INC. is seeking a highly skilled and knowledgeable Industrial Engineer to join our team as part of our innovative drone delivery project. As an Industrial Engineer specializing in machine learning, the applicant will play a crucial role in the development, implementation, and optimization of machine learning algorithms and models to enhance our drone delivery system's efficiency, safety, and reliability.

The applicant's responsibilities will include designing, developing, and implementing machine learning algorithms and models to optimize various aspects of the drone delivery system, such as route planning, navigation, obstacle avoidance, and payload management. The applicant will analyze large datasets collected from drones and other sources to identify patterns, trends, and insights that can improve the performance and effectiveness of the machine learning algorithms. Furthermore, the applicant will be tasked with training, testing, and validating machine learning models using appropriate techniques and methodologies, ensuring high accuracy and reliability under different operating conditions and environments. The applicant will collaborate with software engineers, drone engineers, and other team members to seamlessly integrate machine learning algorithms into the drone delivery system's software and hardware components. The applicant’s role also involves continuously optimizing machine learning models and algorithms to improve performance metrics such as delivery time, energy efficiency, safety, and scalability. The applicant will document all aspects of machine learning development, including algorithms, models, datasets, experiments, and results, and prepare reports and presentations to communicate findings and recommendations to stakeholders.

To qualify for this position, the applicant must hold a Master’s degree in Industrial Engineering & Operations Research. Demonstrated experience in industrial engineering, operations research, and financial engineering. Proficiency in programming languages used in financial analysis, including Python, R, and MATLAB, is required. Strong analytical and problem-solving skills, along with excellent verbal and written communication skills, are essential.

● Must have a Master’s degree in Industrial Engineering & Operations Research. 

● Advanced knowledge and experience in industrial engineering, operations research, machine learning, and scientific research. 

● Proficiency in programming languages, including Python, R, SQL, MySQL, and AMPL. ● Understanding in Linear programming: models, basic theory, algorithms, AMPL implementation, sensitivity analysis. 

● Proficiency in Mixed linear integer models: using binary variables to model logical constraints, covering, packing, partitioning sets models, and basic strategies for solving mixed linear integer problems. 

● Strong understanding in optimization, Big Data, NoSQL, Key-Value data models, MapReduce, Hadoop, Spark, and methods for referencing temporal, geometric, and encrypted data. 

● Completed graduate courses in Relational Databases, using Entity-Relationship Diagrams, relational algebra, SQL, and Normalization Theory. 

● Fundamental concepts and tools for modeling and analyzing stochastic systems. 

● Knowledge of conditional probability and expectation, exponential distribution, and Poisson processes. Basics in simulations, maximum likelihood estimations, and MCMC. ● Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams, derive innovative project management, and develop strategies to maximize personal/team performance. 

● Ability to convey technical expertise with enthusiasm, confidence, and sincerity necessary to build long-term professional relationships. 

● Capable of using clear, concise, meaningful, and persuasive language to share technical knowledge with stakeholders in varied cultural and organizational settings.

The Industrial Engineer specializing in machine learning at MATRIXELLENT INC. is tasked with multifaceted and technically intricate responsibilities within the Drone Delivery project: 

● Engage in the development, implementation, and optimization of sophisticated machine learning algorithms aimed at enhancing the efficiency, safety, and reliability of our drone delivery system. This includes architecting algorithms for route optimization, path planning, obstacle detection and avoidance, and dynamic payload management. 

● Conduct extensive data analysis leveraging large-scale datasets obtained from drones and various sources to discern intricate patterns and insights pivotal for refining algorithmic performance. This involves employing advanced statistical techniques and libraries such as Pandas, NumPy, and SciPy in Python for data manipulation and analysis. 

● Collaborate closely with interdisciplinary teams comprising software engineers, drone engineers, and other specialists to seamlessly integrate advanced machine learning models into the delivery system's software and hardware infrastructure. Utilize Python frameworks like TensorFlow or PyTorch for the development and deployment of machine learning models. 

● Continuously iterate and fine-tune machine learning models to enhance key performance indicators such as delivery throughput, energy efficiency, operational safety, and scalability. Employ techniques such as hyperparameter tuning and ensemble learning to optimize model performance. 

● Conduct rigorous model validation and testing under diverse operational conditions to ensure robustness and reliability. This involves designing comprehensive experiments, meticulously collecting data, and performing meticulous performance evaluations using Python libraries like scikit-learn. 

● Generate comprehensive documentation encompassing algorithmic designs, model architectures, dataset characteristics, experimental methodologies, and analysis outcomes. Utilize tools like Jupyter Notebooks and Markdown for documentation, and prepare detailed reports and presentations to effectively communicate findings, insights, and recommendations to stakeholders. 

● Articulate complex technical concepts with precision and clarity to both technical and non-technical audiences, fostering understanding and alignment across diverse stakeholders. 

● Engage in collaborative efforts with regulatory bodies and industry partners to navigate complex legal and operational landscapes associated with drone delivery. This includes ensuring compliance with stringent safety regulations, establishing robust communication protocols between drones and ground control stations, and addressing intricate logistical challenges inherent in aerial delivery systems. 

● Furthermore, proficiency in supply chain optimization techniques and tools like Linear Programming and Mixed-Integer Linear Programming (MILP) is crucial. This involves leveraging optimization libraries like PuLP or Gurobi in Python to model and solve complex supply chain optimization problems.

● Competitive salary commensurate with experience. 

● Comprehensive health benefits package. 

● Paid time off and holidays. 

● Professional development opportunities.

To apply, please submit your resume to admin@matrixellent.com or click the button below to apply on the website.

Matrixellent Inc. is an equal opportunity employer and encourages applications from individuals of all backgrounds.

Date Posted: 01/10/2024