INFOPARK

Technical Project Manager (Senior )

Tranzmeo is hiring a Technical Project Manager (Senior) with 10+ years of experience to lead cross-functional engineering programs for its AI + fibre-optic sensing products. This role combines deep technical leadership (candidate must have strong hands-on development experience earlier in their career, preferably with Python and front-end technologies), program management, and domain coordination across product, hardware, cloud, and field operations teams. The right candidate will translate product vision into delivery plans, remove technical blockers, and drive high-quality releases that operate in industrial, mission-critical environments.

Location: Kochi (Infopark) — with periodic travel to field sites and to US office (Houston) as required.
Employment type: Full-time, senior individual contributor / people-lead depending on candidate profile.

Key responsibilities

1. Program leadership & delivery
* Own end-to-end delivery of one or more product modules (e.g., T-Connect OneView features, STS enhancements, uptime monitoring).
* Create and maintain product roadmaps, release plans, milestones, risk logs and cross-team dependency maps.
* Run agile ceremonies, sprint planning, PI planning and retrospectives; ensure predictable cadence.
2. Technical leadership & hands-on involvement
* Leverage your prior development experience (Python + front-end) to review architecture, contribute to design discussions, and make tradeoffs.
* Work with ML/data teams to operationalize models (data pipelines, feature stores, inference latency, model monitoring).
* Coordinate hardware integration efforts (DAS/DTS devices, edge compute).
3. Stakeholder & customer management
* Act as primary technical contact for enterprise customers (oil & gas, utilities), translating customer requirements to engineering backlog.
* Prepare and present technical status and risk updates to senior leadership and customers.
4. Quality, reliability & field readiness
* Define and enforce non-functional requirements: uptime, observability, incident response, and on-field diagnostics.
5. People & process
* Mentor engineering teams, run technical interviews, and help grow the engineering team.
* Improve development processes for faster, safer releases in a hardware-coupled product environment.

Required (must-have) qualifications

* Experience: 10+ years total professional experience, with 5+ years in technical/project leadership roles (program/engineering manager, tech lead, etc.).
* Early development background: Strong hands-on development experience earlier in career — Python required, plus proven front-end experience (React/Angular/TypeScript or similar). You should be comfortable jumping into development discussions.
* Education: B.Tech / B.E. in Computer Science, Information Technology, or equivalent (strict requirement).
* Domain familiarity: Experience with AI/ML product delivery, data engineering, or industrial IoT is strongly preferred
* Systems understanding: Experience with distributed systems, real-time processing, and integrating cloud + edge components (AWS/GCP/Azure).
* Delivery skills: Proven Agile / Scrum delivery track record and ability to run complex cross-functional programs.
* Communication: Excellent verbal and written communication; experience liaising with senior stakeholders and customers.

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).
* Bachelor’s or Master’s 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 3–5 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 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).
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 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.

Data Science Intern

Explain the predictive models to various business users and make recommendations to drive business strategy
Make recommendations to resolve application performance problems
Implement data processing methods and tools
Collaborate with product leaders, subject matter experts, and decision-makers to develop success criteria and optimize new products, features, policies, and models
Leverage your experience in analytics tools and scientific rigor to produce actionable insights
Distill and communicate key insights to senior management in verbal, visual, and written media
Together with the Co-op department lead, determine an appropriate data science problem statement and toolset to apply during the co-op term
Determine strengths and weaknesses of data science toolsets and procedures
Qualification
Knowledge of Machine Learning concepts (cross-validation, regularization, boosting, bootstrapping) is a plus
Working on a degree in Computer Science, or a related field, with project experience in data analysis
Experience with big data technologies (Hadoop, Hive, MongoDB, Spark)
Experience with statistical analysis and data mining using tools such as R, SAS, Matlab, Stata, or SPSS

Junior Geophysicist- Fiber-optic Sensing & AI (Fresher)

We are seeking a motivated Junior Geophysicist (recent graduate) to dive into projects involving Distributed Acoustic Sensing (DAS), fiber‑optic sensor data, and Python‑driven AI analysis. You’ll work closely with geophysicists, data scientists, and engineers to drive data‑centric insights and support field deployments.

Key Responsibilities
Support data acquisition, preprocessing, and interpretation from fiber‑optic sensing systems (DAS/DTS).

Analyze large time‑series datasets using Python (NumPy, Pandas, SciPy, Matplotlib).

Collaborate with AI/ML experts to build models for signal classification, event detection, or anomaly identification.

Participate in field activities, including deploying sensors, monitoring systems, and validating datasets.

Document workflows, results, and technical insights clearly in reports or code comments.

Required Qualifications
Bachelor's or Master's degree in Geophysics, Geoscience, Physics, Engineering, or related discipline.

Fundamental understanding of seismic wave behavior and fiber‑optic sensing principles.

Basic proficiency in Python and experience with data‑analysis libraries.

Interest in machine learning—any exposure to scikit‑learn, TensorFlow, or PyTorch is a plus.

Excellent analytical thinking, communication skills, and collaborative mindset.

Preferred (Nice-to-Have)
Experience with signal processing, time‑series analysis, or seismic inversion methods.

Familiarity with version control systems (e.g., Git) and Jupyter notebooks.

Willingness and physical ability to participate in occasional fieldwork and travel.

What You’ll Gain
Hands‑on experience at the intersection of geophysics, fiber‑optic sensing, and AI.

Mentorship from industry professionals and cross‑disciplinary collaboration.

Exposure to real‑world problems in energy, infrastructure, and environmental monitoring.

Customer Success Manager

We are seeking an experienced Customer Success Manager to join our team. The candidate will play a key role in ensuring customer satisfaction, delivering client engagement excellence, and driving customer success through proactive measures.

Key Responsibilities
Act as the primary point of contact and trusted advisor for customers
Develop and nurture long-term relationships with the Customer stakeholders
Understand Customer requirements and business goals
Ensure frictionless onboarding & adoption of Tranzmeo’s product/solution.
Proactively review and manage customer accounts for greater Customer satisfaction and long-term retention.
Track & get the customer issues resolved promptly and effectively, escalating when necessary.
Conduct regular review meetings with the customer to provide insights on product usage and best practices.
Collaborate with cross-functional Tranzmeo teams (Sales, Product, Support) to ensure a seamless customer experience.
Regularly monitor customer account health metrics and implement strategies to mitigate business risks
Develop new knowledge assets based on experiential insights from Customer engagements
Gather business insights of Customer needs and drive upsell/cross-sell opportunities

Required Skills & Qualifications
Education: B.Tech degree (mandatory).
Experience: Minimum 7 years of relevant experience in Customer Success Management, Customer Delivery Management, or Customer Relationship Management.
Excellent communication and interpersonal skills.
Language Proficiency: Fluency in English and Hindi is mandatory.
Strong problem-solving and negotiation abilities.
Ability to manage multiple clients and priorities effectively.
Ability to quickly learn about the software products/solutions to guide clients in their business context
Familiarity with CRM tools and customer success platforms.

What We Offer
Competitive salary and benefits.
A dynamic, respectful, and growth-oriented professional environment.
Opportunities for Career development and skill enhancement
Opportunities to gain highly valued professional experiences