AI / ML Developer (Lead) with skills AI/ML Development, TensorFlow for location Bangalore, India

You are joining as a Founding Member of the Infogain LE Center of Excellence (CoE). In addition to being the Primary Subject Matter Expert (SME) for Hindi/English, you will play a critical role in operationalizing the Linguistic Engineering practice. You will partner directly with AI leadership to define the workflows, quality standards, and governance frameworks that will scale to support Meta's global linguistic operations.

Founding Team Responsibilities (The Builder Scope)

Process Architecture & Workflow Design:

. Define The Way We Work (SOPs): You will author the initial Standard Operating Procedures (SOPs) and Living Playbooks. You must transform abstract client requirements into repeatable, step-by-step engineering processes that junior linguists can follow.

. Guideline Calibration: Establish the Golden Standard for annotation guidelines. You will create the master documentation that language PODs / third-party vendors use to create annotated data, ensuring ambiguity is minimized.

Operational Governance & Quality Assurance:

Quality Frameworks: Design the protocols for Statistical Quality Control (SQC) and Deep-Dive Audits. You will define how we measure Inter-Annotator Agreement (IAA) and when we trigger a corrective action.

Root Cause Analysis (RCA) Standards: Develop the templates and logic trees for diagnosing model failures. You will set the standard for distinguishing between a Data Error, a Logic Bug, and a Model Hallucination.

Metric Definition: Help define and track the KPIs for the practice, specifically regarding Quality (F1 Score, Accuracy) and Delivery (Throughput), to ensure the CoE meets client SLAs.

Talent Acquisition & Scaling:

. The Gatekeeper: Design the technical screening interview for future Linguistic Engineers (Indic & Global). You will conduct technical assessments to ensure incoming hires meet the Linguist as Engineer bar.

. Training: Create the onboarding curriculum to upskill traditional linguists into computational roles.

Strategic Advisory & Pre-Sales:

. Proposal Support: Collaborate with the Field CTO and Sales leadership to provide technical inputs for client proposals (RFPs), pilots, and Proofs of Concept (POCs).

. Client Red Teaming: Proactively analyze pilot models (e.g., Llama 3 for Hindi) to identify failures before the client points them out, demonstrating proactive thought leadership.

Core Execution Responsibilities (Hindi / English Specialization)

(You must still demonstrate Hands-on capability to lead by example)

Linguistic Reality of Hindi & Indian English (Illustrative Examples)

Note: The following examples highlight the technical depth required for this role. Actual responsibilities may evolve as we uncover new model failure modes.

Phonology & ASR: Manage complex acoustic modeling challenges, such as Schwa Deletion in Hindi (e.g., Rama vs. Ram) and Indian English accent shifts (e.g., retroflexion, syllable timing) to ensure accurate G2P alignment.

Code-Mixing (Hinglish): Design robust logic for Romanized Hindi in data and improve Language Identification (LID) triggers for speakers switching between Hindi and English mid-sentence.

Syntax & Morphology: Solve high-complexity NLU failures for example those caused by Split-Ergativity (usage of the ne marker) and structural divergence between Hindi (SOV) and English (SVO).

Cultural Ground Truth: Curate Golden Sets that capture strictly local context to fix localization gaps.