AI & ML Engineer (Senior)

AI &?ML Engineer (Senior)

Location : Kochi / Infopark Phase II Campus

Experience & Educational Requirements

* Minimum of 7 years relevant experience in AI/ML engineering, data science or related roles (industry or product?engineering).

* Bachelors or Masters degree in Computer Science, Information Technology or similar.

* Strong preference: B.Tech/M.Tech in CSE/IT or equivalent and good depth in data structures, algorithms, mathematics for ML.

* Demonstrable track record of building and deploying ML models in production (for at least 35 years within the 7+).

* Experience in product?oriented work (versus purely research) is advantageous.

Key Responsibilities

* Lead the design, development, implementation and optimization of machine learning, deep learning and anomaly?detection models to power Tranzmeos 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).

* Keep abreast of latest developments in ML/AI (especially anomaly detection, streaming analytics, sensor?signal processing, edge ML) and bring actionable innovation into the companys 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 companys deep?tech orientation).

Required Technical Skills

* 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.

Desired Additional Skills / Attributes

* 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 Tranzmeos culture (entrepreneurial outlook, independent thinking)

* Leadership / mentoring ability: able to guide junior engineers, elevate teams 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.

How to Apply:

Interested candidates can send their updated resume tolakshmi@tranzmeo.comwith the subject line

AI &?ML Engineer (Senior).

Apply now or DM me to learn more!