We are seeking a Senior AI & ML Engineer with 7+ years of experience to lead the design, development, and deployment of advanced machine learning and anomaly detection models for industrial/IoT applications.

Skills

• Programming
• data structures & algorithms
• ML Expertise
• Data Engineering
• Communication
• Collaboration Skills

Requirements

• Job Role AI & ML Engineer-Senior
• Job Type Full Time
• Workplace Type Onsite
• Industry Software Development

Secondary locations

About

Not provided

Responsibilities

•  Lead the design, development, implementation and optimization of machine learning, deep learning and anomaly‑detection models to power Tranzmeo’s flagship product (e.g., “T‑Connect OneView”) and other AI solutions for industrial/IoT infrastructure.
• Work end‑to‑end: Data ingestion, cleaning, feature engineering, model training, evaluation, deployment (edge/cloud/hybrid) and monitoring.
•  Collaborate with hardware/edge teams (e.g., fiber‑optic sensing, DAS/DTS data streams) to integrate signal / sensor data pipelines, enabling real‑time/near‑real‑time anomaly detection.
•  Build scalable architectures for AI/ML workflows – covering large volumes of streaming data, distributed processing, possibly edge‑computing constraints.
• Mentor junior ML/data engineers, review code, design best practices, enforce engineering discipline (unit‑testable code, model versioning, reproducibility).
• Engage with cross‑functional stakeholders (product management, domain experts in oil & gas/infrastructure, field engineering) to translate business or operational problems into ML solutions, and iterate model outcomes.
• Keep abreast of latest developments in ML/AI (especially anomaly detection, streaming analytics, sensor‑signal processing, edge ML) and bring actionable innovation into the company’s tech stack.
• Contribute to technical architecture decisions, choosing frameworks/libraries/tools (e.g., Python ecosystem, TensorFlow/PyTorch, streaming frameworks, cloud/edge deployment).
• Measure model performance in production, define KPIs for detection/false‑alarm rates, maintain model drift tracking, identify when to retrain/refine.
•  Document designs, maintain clear version control, ensure reproducibility of experiments, and manage model lifecycle.
• Assist in patenting, IP documentation or presenting internal/external publications/workshops (given the company’s deep‑tech orientation).

Other Requirements

• Excellent proficiency in Python (including libraries such as NumPy, Pandas, Scikit‑Learn, etc.).
•  Strong programming skills: algorithmic thinking, data structures, software engineering fundamentals, version control (Git), code reviews.
•  Deep experience in ML/AI: supervised, unsupervised, anomaly detection, time‑series, streaming data, deep learning (CNNs, RNNs/LSTM, transformers if applicable).
•  Experience with sensor data, large scale data ingestion/processing pipelines, streaming analytics (e.g., Kafka, Spark Streaming, Flink) is a plus.
•  Knowledge of deployment of ML models: either cloud (AWS, Azure, GCP) or edge/hybrid, model serving frameworks, monitoring tools.
•  Familiarity with IoT/industrial data domains (e.g., pipelines, remote sensing, fiber‑optic sensors) is highly desirable – domain knowledge will accelerate impact.
•  Strong mathematics/statistics background: probability, linear algebra, optimization, hypothesis testing, performance metrics ROC/AUC etc.
•  Ability to write clean, maintainable engineering code (not just notebooks) and collaborate with software / embedded teams.
•  Good communication skills for liaising with non‑ML stakeholders, explaining model outcomes, presenting results.

Good to have

• Experience with anomaly detection frameworks and techniques specific to industrial systems, remote sensing, intrusion detection.
• Experience with big data technologies (Hadoop/Spark, NoSQL, time‑series databases) and large scale datasets (millions of records)
• Familiarity with edge computing constraints: model size, latency, hardware sensors, embedded systems.
• Intellectual curiosity, startup mindset: able to work in a growing, somewhat lean organisation, comfortable with ambiguity, taking initiative. This aligns well with Tranzmeo’s culture (“entrepreneurial outlook”, “independent thinking”)
• Leadership / mentoring ability: able to guide junior engineers, elevate team’s capability.
• Strong problem‑solver: able to pick up domain knowledge rapidly (oil & gas/infrastructure), translate business problem into ML pipeline.
• Good documentation, reproducibility mindset, focus on production readiness (not just prototyping).
• Willingness to travel or work with field data, deploy models in industrial settings if needed.

About the Company

Tranzmeo - Towards a smart tomorrow! We, Tranzmeo is an anomaly forensics company, based out of gods own country kerala, that endeavours to reshape remote sensing and anomaly detection with technology and innovation. Here, we believe and work for the ideas that could transform the world. With its advanced remote monitoring system, Tranzmeo Connect OneView, Tranzmeo aims to forefront the digital evolution. T-Connect Oneview, powered by the advanced technologies of AI, ML, and Fibre optic sensing, is India’s first advanced solution for anomaly and intrusion detection. T-Connect OneView operates in pipelines, rails, subsea, smart roads, LNG, power cables and border security across the country. Tranzmeo kickstarted its official journey in 2017, under the leadership and guidance of our Founder, Mr. Safil Sunny. The impeccable growth and achievements of the company continue every year, motivating many aspiring startups. Widening our horizon, Hindustan Petroleum Corporation Limited , a Maharatna Status and a Forbes 2000 company, has also become a valuable partner of Tranzmeo. Our Tranzmeo family is built on core values of integrity, hard work, commitment and excellence. Encouraging talents, Tranzmeo keeps on upgrading ourselves for a better and smart future.