Customer Success Associate

The Role

You own AI systems end to end. From the speech-to-text models that turn audio into text, to the diarization that separates and identifies speakers, to the agentic layer that turns conversation into memory and action, to the observability and evaluation that keep all of it honest in production. This is a wide role by design. You will own model selection, serving, and production reliability. If you want to tune one model and ignore the system around it, this is not the role.

What You Will Own

•     Speech-to-text. Evaluate, integrate, and optimize STT models across cloud and self-hosted. Drive accuracy and cost trade-offs with ground-truth metrics.

•     Speaker diarization and identification. Push accuracy on hard, real-world, multi-speaker audio.

•     Agentic AI. Build the memory and retrieval pipeline, LLM orchestration, and the agent workflows that sit on top of captured conversation.

•     Model serving and infrastructure. Stand up and optimize self-hosted serving (vLLM, Triton class). Own latency, throughput, and cost per user.

Observability

An always-on wearable means models run in production every second, on messy real-world audio. You own the visibility into that.

•     Instrument the full audio-to-memory pipeline: STT, diarization, retrieval, and LLM calls.

•     Define and track model-quality SLOs in production: transcription drift, diarization error over time, retrieval relevance, latency, throughput, and cost per user.

•     Build dashboards and alerting so model degradation is caught before users feel it.

•     Trace failures across a distributed, always-on system using metrics, logs, and traces.

•     Close the loop. Production signals feed back into evaluation and model selection.

Evaluation

We do not ship what we cannot measure. You own the systems that prove a model is actually better, not just newer.

•     Build and own ground-truth evaluation harnesses for every model in the stack.

•     Measure with real metrics: WER for transcription, DER for diarization, Recall and F1 for retrieval and speaker identification.

•     Build and maintain labeled benchmark datasets that reflect real, messy, multi-speaker audio.

•     Run regression and A/B evaluations on every model swap, prompt change, or pipeline update. Nothing ships on a vibe.

•     Reject anecdotal proxies, single confidence scores, and cherry-picked examples as evidence of quality.

What We Are Looking For

•     3 to 5 years as an AI/ML engineer with production systems behind you. Engineering and production experience is non-negotiable.

•     Depth across the modern AI stack: LLMs, speech models, vector retrieval, model serving.

•     Strong software engineering. You write code that ships and survives contact with real users.

•     Fluency in Python and the production ML ecosystem.

•     Comfort with cloud infrastructure (GCP a plus) and containerized deployment on Kubernetes.

•     A working command of observability and evaluation. You measure first and trust metrics over intuition.

•     First-principles reasoning and metric discipline.

Nice to Have

•     Research background or publications. A strong signal, not a substitute for production work.

•     Audio and speech ML experience (STT, diarization, voice).

•     Experience self-hosting and optimizing open models.

•     Experience with LLM gateway and agent orchestration patterns.

•     Experience building eval harnesses or production model-monitoring systems.

Requirements

Agentic work is must. Audio is good to have

. Self hosting models is a must

 Experience with LLM gateway and agent orchestration is a must have

Role Overview

We are looking for a Delivery Supervisor – Last Mile to own and deliver a white-glove, hassle-free delivery and installation experience. This role requires the individual to be physically present at customer sites on delivery days, acting as the single point of accountability for end-to-end last-mile execution.

This is a hands-on, execution-focused role ideal for candidates with experience in furniture delivery, installation coordination, or site supervision.

Key Responsibilities

• Be present at the customer location during scheduled delivery and installation.
• Act as the single point of ownership for end-to-end last-mile execution.
• Ensure products are delivered, unpacked, assembled, and installed as per approved drawings and specifications.
• Coordinate in real time with OEM/vendor dispatch teams, installers, carpenters, technicians, and logistics partners.
• Ensure on-time arrival, correct installation sequencing, and minimal waiting time at site.
• Represent the brand professionally and communicate timelines and next steps clearly to customers.
• Inspect products for transit damage, finish issues, or missing parts prior to installation.
• Ensure safe handling of furniture, site cleanliness, and protection of customer property.
• Resolve on-ground issues independently and escalate only when necessary.
• Update delivery status, issues, and customer feedback accurately in internal systems.

Success Metrics (KPIs)

• On-time delivery and installation percentage
• First-time-right installation rate
• Customer satisfaction / NPS at delivery stage
• Damage and rework incidence
• Number of escalations per delivery

Ideal Candidate Profile

• Experience in last-mile delivery, installation, or site coordination (furniture or interiors preferred)
• Strong coordination and stakeholder management skills
• Customer-first mindset with high attention to detail
• Calm, solution-oriented approach in high-pressure situations
• Willingness to travel and be on-site for deliveries

Your Day-to-Day Role:

• Design and implement web applications from initial concept, architecture design, to completed, operational software.
• Lead complex engineering tasks where you’ll act as the technical authority.
• Contribute to code reviews and continuous integration.
• Adapt and apply cutting edge technologies.
• Collaborate with other engineers, designers, and product owners to define elegant customer solutions.
• Ensure robustness by writing automation tests for your code.

What Are We Looking For:

At least 3 years of professional experience in Fullstack development.

Mandatory Technical Skills

• Robust experience in MERN Stack (MongoDB, ExpressJS, ReactJS, NodeJS). Expertise in ReactJS, Redux, HTML, CSS.
• Proficiency in Javascript (ES6) and TypeScript.
• Hands-on experience in Socket Implementation.
• Solid understanding of GIT and its workflows.

Good to Have Skills (Optional)

• Familiarity with Material UI.
• Experience with HTML Canvas APIs (Ex: KonvaJS for canvas drawing).
• Basic understanding of AWS services (S3, Redis, Lambda, Messaging services, etc.). 

• General Accounting
• Account Payable/Account Receivable
• Debit/credit, reconciliation
• Bank Receivable and Bank Payable.
• TDS, Tax rules
• Balance sheet
• Bank and other reconciliation's

passion for building and delivering great software with a strong sense of ownership.

• 4+ years of experience in building web applications using React, Node.js, GraphQL integrations with NoSQL or relational database systems.
• Working experience in building and deployment applications on AWS platform a plus.
• Working experience on docker and microservice a plus.
• Strong experience with Build and Release, Agile processes and Estimation/Planning
• Must have strong debugging and troubleshooting skills, with solid understanding of logging and exception handling. 

• Proficient with Laravel & Codeignitor Framework 
• Have good database structures and algorithm platform
• Knowledge about OPP, MVC, RESTful
• Knowledge about HTML, CSS, JavaScript, AngularJS, ActiveJS, NodeJS, JQuery is an advantage
• Have experiences using GIT
• Use fluently one of relation database administration: Oracle, MySQL