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Statistical signal processing jobs

2+ Statistical signal processing Jobs in India

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Semi-Conductor Industry

Semi-Conductor Industry

Agency job
via Peak Hire Solutions by Dhara Thakkar
Hyderabad
10 - 12 yrs
₹30L - ₹35L / yr
Signal integrity
Systems analysis and design
Schematic
skill iconPython
Perl
+113 more

MANDATORY CRITERIA:

  • Education: B.Tech / M.Tech in ECE / CSE / IT
  • Experience: 10–12 years in hardware board design, system hardware engineering, and full product deployment cycles
  • Proven expertise in digital, analog, and power electronic circuit analysis & design
  • Strong hands-on experience designing boards with SoCs, FPGAs, CPLDs, and MPSoC architectures
  • Deep understanding of signal integrity, EMI/EMC, and high-speed design considerations
  • Must have successfully completed at least two hardware product development cycles from high-level design to final deployment
  • Ability to independently handle schematic design, design analysis (DC drop, SI), and cross-team design reviews
  • Experience in sourcing & procurement of electronic components, PCBs, and mechanical parts for embedded/IoT/industrial hardware
  • Strong experience in board bring-up, debugging, issue investigation, and cross-functional triage with firmware/software teams
  • Expertise in hardware validation, test planning, test execution, equipment selection, debugging, and report preparation
  • Proficiency in Cadence Allegro or Altium EDA tools (mandatory)
  • Experience coordinating with layout, mechanical, SI, EMC, manufacturing, and supply chain teams
  • Strong understanding of manufacturing services, production pricing models, supply chain, and logistics for electronics/electromechanical components


DESCRIPTION:

COMPANY OVERVIEW:

The company is a semiconductor and embedded system design company with a focus on Embedded, Turnkey ASICs, Mixed Signal IP, Semiconductor & Product Engineering and IoT solutions catering to Aerospace & Defence, Consumer Electronics, Automotive, Medical and Networking & Telecommunications.


REQUIRED SKILLS:

  • Extensive experience in hardware board designs and towards multiple product field deployment cycles.
  • Strong foundation and expertise in analyzing digital, Analog and power electronic circuits.
  • Proficient with SoC, FPGAs, CPLD and MPSOC architecture-based board designs.
  • Knowledgeable in signal integrity, EMI/EMC concepts for digital and power electronics.
  • Completed at least two project from high-level design to final product level deployment.
  • Capable of independently managing product’s schematic, design analysis DC Drop, Signal Integrity, and coordinating reviews with peer of layout, mechanical, SI, and EMC teams.
  • Sourcing and procurement of electronic components, PCBs, and mechanical parts for cutting-edge IoT, embedded, and industrial product development.
  • Experienced in board bring-up, issue investigation, and triage in collaboration with firmware and software teams.
  • Skilled in preparing hardware design documentation, validation test planning, identifying necessary test equipment, test development, execution, debugging, and report preparation.
  • Effective communication and interpersonal skills for collaborative work with cross-functional teams, including post-silicon bench validation, BIOS, and driver development/QA.
  • Hands-on experience with Cadence Allegro/Altium EDA tools is essential.
  • Familiarity with programming and scripting languages like Python and Perl, and experience in test automation is advantageous.
  • Should have excellent exposure with coordination of Manufacturing Services, pricing model for production value supply chain & Logistics in electronics and electromechanical components domain.
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Oil & Energy Industry

Oil & Energy Industry

Agency job
via Green Bridge Consulting LLP by Susmita Mishra
NCR (Delhi | Gurgaon | Noida)
1 - 3 yrs
₹8L - ₹12L / yr
skill iconMachine Learning (ML)
skill iconData Science
skill iconDeep Learning
Digital Signal Processing
Statistical signal processing
+6 more
Understanding business objectives and developing models that help to achieve them,
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying
differences in data distribution that could affect performance when deploying the model
in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production
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