Ask HN: Who wants to be hired? (February 2026)

Location:- Ithaca, New York Remote:- Preferably Onsite but open to it. Willing to Relocate :- Yes Technologies :- C/C++, Python, Verilog( good understanding), ROS2, STM32, RP2040, FPGA, Ardupilot, RTOS, MODBUS, Profinet, CAN, RS-232/UART, I2C, SPI, JTAG, TCP/IP, UDP, AV over IP, LiDAR, YOLOv3, PCB Design, Git,IOT ,hardware software system design Resume :- https://drive.google.com/file/d/1NVPAQ_msfDjuZ4b2I61Ed5pXDUD... Email:- iv74@cornell.edu Linkedin :- https://www.linkedin.com/in/immanuel-varghese-koshy/

Remote: Optional

Willing to relocate: Yes, worldwide

Technologies: Python, Matlab Email: marthaelias [at] protonmail [dot] com Github: https://github.com/marthafay My Contribution (Short Profile):

- Applied Al research with focus on real-time signal processing, decision logic & anomaly detection - Modular signal & system architecture — complements classical ML stacks - SDKs: Audio, Finance - Physically informed analogy modules (e.g., superposition in Python) • Hand-crafted, explainable features & operators • Guiding principle: ML/RL cleanly embedded into a predefined architecture Example Result Phase-aware XGBoost trained on "Melodic House" harmonies → showed genre generality beyond training data Working Principle Reproducible research: clear pipelines, paper-style notebooks, deterministic exports Mainstream Deep Learning (TensorFlow) - Purpose: ML, Deep Learning, neural networks • Focus: Classification, regression, prediction • Architecture: Computation graph & tensors • Inputs: n-dim tensors • Outputs: Probabilities, models, vectors • Computational Principle: Gradient descent • Components: Layers, losses, optimizers • Tooling: GPU-first workflows, tf.keras, deployment stacks • Data Strategy: Big Data, automatic feature learning • Explainability: Often low (requires additional tooling) • Style: GPU-heavy, often overdimensioned • Versioning: Model checkpoints, weights

Location: Burlington, MA Remote: Optional Willing to relocate: Yes Technologies: Python, React, JavaScript, SQL, REST APIs, Git, CI/CD, PySide6 Résumé/CV: https://drive.google.com/drive/folders/1GkZceihbtVWolNuupmp5...

Email: sathmangazi1@gmail.com

Summary: Software Engineer with ~2 years of experience building internal enterprise systems in a manufacturing environment. At Novanta, I built LiteMES, a Python/PySide6/MSSQL manufacturing execution system used by 100+ operators and engineers, replacing manual red-tag and Excel workflows and improving sprint delivery from ~90% to ~97%.

I work end-to-end: requirements → system design → implementation → deployment → user adoption. Strong bias toward pragmatic, business-driven engineering.

Outside of my core SWE role, I also run a small influencer marketing side project, where I handle creator outreach, deal negotiation, campaign tracking, and performance analysis for consumer brands. This has strengthened my skills in data-driven decision making, communication, and building systems that connect technical execution with revenue outcomes.

Orca Security Ambassador. Currently on H-1B grace period and seeking transfer sponsorship. Open to backend, full-stack, or product-driven engineering roles.

Previously, I accelerated a 1.5-year career track , becoming the first intern in the team's history to earn a promotion to Systems Engineer. In this role, I architected solutions for the EV and battery swapping space, specifically for heavy electric vehicles, contributing to 7+ pending patents. I also served as Vice-Captain of an SAE Aero Design team, leading the development of autonomous aircraft and ground vehicles to achieve a World Design Rank of 3rd. Currently a final semester Master of Engineering student in Electrical and Computer Engineering at Cornell University.

Location: Philadelphia, PA, USA

Remote: Yes

Willing to relocate: Yes

Technologies: Python, C++, C, CUDA, Computer Vision, Post training, Reasoning, Robotics, Multimodal sensing, Deep Learning, Event cameras

Résumé/CV: https://www.seas.upenn.edu/~richeek/assets/pdf/RicheekCV.pdf

Email: richeek@seas.upenn.edu

I am looking for internships -- summer/fall 2026.

My PhD work is on robotics, computer vision, neuromorphic and multimodal sensing, and representation learning.

I am excited about opportunities to work on robotic perception and planning (with multiple sensors, representation learning, world models, etc) -- and -- reasoning (post-training, etc).