R&D Engineer

Position Summary

We are seeking a highly motivated and intellectually curious R&D Engineer to join our dynamic Software development team. In this role, you will be pivotal in exploring and developing new technologies centered around the vast datasets generated by our IoT devices.

You will be responsible for the full R&D lifecycle: from conceptualization and data exploration to building proof-of-concepts (PoCs) and prototypes. The ideal candidate is a
fast learner

with a strong
aptitude for R&D

, a passion for
new technologies

, and a deep-seated curiosity about
data

. If you thrive on solving complex problems, are
always up for a new challenge

, and want to work at the intersection of hardware, software, and data science, this is the role for you.

Key Responsibilities

• Innovate & Explore:

Conduct applied research into new methods, algorithms, and technologies for processing, analyzing, and deriving value from large-scale IoT sensor data (e.g., time-series analysis, sensor fusion, predictive modeling).
- Prototype & Develop:

Design, build, and test proof-of-concepts (PoCs) and minimum viable products (MVPs) that apply data science and machine learning techniques to solve novel challenges.
- Data Pipeline Engineering:

Collaborate with data engineers to design and implement experimental data pipelines for ingesting, storing, and processing high-velocity IoT data streams.
- Analyze & Model:

Apply statistical analysis and machine learning models (e.g., predictive maintenance, anomaly detection, behavioral analytics) to extract actionable insights from complex datasets.
- Technology Scouting:

Continuously monitor and evaluate emerging technologies, tools, and trends in IoT, data science, MLOps, and edge computing to identify new opportunities for innovation.
- Collaborate & Communicate:

Work closely with cross-functional teams (product managers, software engineers, hardware engineers) to define research questions, iterate on solutions, and communicate complex findings clearly and concisely.
- Document & Transfer:

Document research findings, experimental procedures, and prototype designs to facilitate knowledge transfer to engineering and product teams.

Required Qualifications & Skills

• Education:

Bachelor's degree in Computer Science, Electrical/ Computer Engineering or Data Science.
- Experience:

0-3 years of experience in an R&D, data science, or software engineering role.
- Data Science:

Strong proficiency in data analysis and machine learning using Python (with libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
- Data Engineering:

Experience with data querying languages (e.g., SQL, NoSQL) and familiarity with data processing technologies (e.g., Spark, Kafka, or similar).
- IoT Familiarity:

Solid understanding of IoT concepts, sensor data characteristics (e.g., time-series, high-frequency), and communication protocols (e.g., MQTT, CoAP).
- Problem Solver:

Demonstrated ability to tackle complex, ambiguous problems with a structured, analytical approach.
- Core Attributes:

Proven
fast learner

, naturally curious, and a self-starter who is
always up for a new challenge

.

Preferred Qualifications

• Education:

Bachelor's or Master's in a relevant field.
- Advanced ML:

Experience with deep learning (e.g., LSTMs, CNNs for time-series) or reinforcement learning.
- Cloud & Big Data:

Hands-on experience with cloud platforms (AWS, GCP, or Azure).
- Edge Computing:

Familiarity with development on edge devices (e.g., Raspberry Pi, IMX, Atheros, Mediatek) or edge AI frameworks (e.g., TensorFlow Lite).
- Software Engineering:

Strong software development practices, including version control (Git), testing, and CI/CD principles.

About PLC Group

PLC Group is a Canadian company that provides a portfolio of Artificial Intelligence based Remote Monitoring & Control IoT solutions and Facilities Modular Planning & Capacity Management Solutions to Mission Critical Facilities, Cable Landing Stations, Cable Operators, Data Centers, Telecom Companies, and Telecom Tower Sharing companies.

PLC portfolio is designed to reduce facilities CAPEX & OPEX through Predictive Maintenance, "right-sizing" cooling and energy capacity in facilities, and faster turnaround on facilities design & capacity planning using real-time sensor data and machine learning.